International Journal of Manufacturing Technology and Management (56 papers in press)

Regular Issues

• Building win-win value networks for product-service systems’ delivery
  by Sophie Peillon, Khaled Medini, Thorsten Wuest 
  Abstract: Product-service systems (PSS) are complex bundles of products and services aimed at fulfilling customers’ needs. The key challenges of designing a new PSS include establishing the underlying value network supporting PSS delivery. The success of a PSS business model relies heavily on establishing a win-win value network that ensures fairly shared value capture and creation among the PSS stakeholders. This paper investigates the underlying challenges of establishing such value networks, and proposes a novel framework for building win-win value networks for PSS delivery. A case study illustrates the applicability and usefulness of the proposed framework in designing and assessing the possible value networks and associated value capture for the delivery of an innovative smart PSS in the cheese industry.
  Keywords: product-service systems; PSS; business model; value network; value capture; economic assessment.
  This article is being considered for Open Access
   
  
• Effect of Machining Parameters in Drilling of Glass Fiber Reinforced Polymer Composite with Modified AJM Process.  
  by Basanta Kumar Nanda, Debabrata Dhupal 
  Abstract: Conventional drilling of Glass Fiber Reinforced Polymer (GFRP) composite produces delamination effect due to peel-up and pull out of the layers. This research work represents drilling of GFRP rectangular workpieces with fluidized bed abrasive jet machining (FB-AJM) process using silicon carbide (SiC) abrasives. Experiments were conducted according to Box-Behnken design matrix to measure the four responses, namely, material removal rate (W), surface roughness (Ra), depth of cut (h), and taper angle (TA) by utilizing bed pressure (P), nozzle tip distance (Z) and abrasive grain size (G) as input parameters. Desirability based particle swarm optimization (PSO) was performed for the multi-objective optimization to find the optimal input parameters P, Z and G of 6 kgf/cm2, 7 mm, 260μm respectively. A single experiment was performed at the predicted optimal conditions to validate the model with minimum error. The SEM analysis of the machined composite surface revealed the initiation and propagation of cracks along with embedment of erodent particle.
  Keywords: Glass Fiber Reinforced Polymer (GFRP); fluidized bed abrasive jet machining (FB-AJM); silicon carbide (SiC); response surface methodology (RSM); Desirability-Function; particle swarm optimization (PSO).
  
  
• FPGA Implementation of Gate Level Modified Adaptive Filter Architecture for Noise Cancellation Application  
  by Gomathi Swaminathan, Murugesan G 
  Abstract: This paper provides an approach for the implementation of modifications in the gate level in the adaptive filter architecture. An adaptive filter is appreciable when processing real time data and under the conditions when the signal statistics are not known a priori. Filtering data in real time needs a dedicated hardware. The resources available for implementing an efficient digital filtering algorithm are present in Field Programmable Gate Array. To design a dedicated hardware with low computational complexity, an approach of gate level modifications is incorporated in the EX-OR gate and the modified EX-OR gate is implemented in the coefficient decimation method. The proposed modified coefficient decimation method is applied in the adaptive algorithms such as Recursive Least Square, Affine Projection, and Kalman algorithm. The designed structures are experimented with the ECG and speech signal and implemented in the Xilinx Virtex 5 FPGA. Simulation and implementation results infer area reduction is achieved up to 50% and delay reduction of 10% is obtained in the proposed structures.
  Keywords: Field Programmable Gate Array; EX-OR; ECG; hardware; XILINX System Generator; full adder; half adder.
  DOI: 10.1504/IJMTM.2017.10011891
   
  
• TWO DIMENSIONAL CUTTING STOCK PROBLEM WITH MULTIPLE STOCK SIZES  
  by Umutcan Ayasand?r, Meral Azizoglu 
  Abstract: In this study, we consider a two dimensional cutting stock problem with multiple stock sizes and two stage guillotine cuts. Our objective is to maximize the difference between total revenue earned over all cut items and total cost spent over all used panels. We propose two mathematical models, derive some optimality properties and use them to enhance the performances of the models. We develop decomposition-based heuristics that use the best of the proposed models to solve the subproblems. The results of our computational study have revealed that the models can return optimal solutions for the instances with up to 30 items in 2 hours and the heuristics produce near-optimal solutions for the instances with up to 50 items in 5 minutes.
  Keywords: Integer Programming; Heuristics; Cutting Stock Problem.
  DOI: 10.1504/IJPS.2021.10043393
   
  
• Reallocation and Imported technology: Evidence from Vietnam manufacturing Sector  
  by Nguyen Khac Minh, Phung Mai Lan 
  Abstract: The objective of this study is to measure the contribution of "high- tech" importers (high-tech firms) to the productivity growth of the Vietnamese manufacturing industry. This analysis uses augmented Olley - Pakes static and dynamic productivity decomposition and the annual panel industrial survey data from the period of 2012-2016. The results indicate that high-tech firms account for only 20.8% of total firms but contribute 59.6% to productivity growth. The static decomposition shows that the reallocation process is an important mechanism for increasing the industrial productivity. The dynamic decomposition indicates that the exiting firms are the factor that reduces productivity growth while learning by doing and improving technology within the firm are limited and only significantly contribute in high-tech firms. The results also shows that high-tech importers not only increase their productivity but also become stronger in the market. The spillover effect from the high-tech firms is stronger than that of foreign-owned firms.
  Keywords: Static and dynamic decomposition; reallocation process; manufacturing industry.
  
  
• Capability management of manufacturing research centres: challenges and opportunities  
  by Olga Uflewska, T.C. Wong, Michael Ward 
  Abstract: This paper is the first to investigate capability management of manufacturing research centres within the High Value Manufacturing Catapult (HVMC). The HVMC was established to address the valley of death by bridging the gap between industry and academia in order to drive the UKs economic and technological growth. However, the current literature does not fully recognise capability management of manufacturing research centres, and hence overlook its link with operations management and strategic management within research centres environment. Regarding technology capabilities, manufacturing companies usually adopt their own measurements or assessment tools such as Technology Readiness Levels (TRL) or Manufacturing Readiness Levels (MRL) to track their technological progression. These tools, however, are not sufficient to devise important capability management practices due to research centres unique operating characteristics. It is evident that standardising such practices within the HVMC is vital, and this drives the need of developing a new capability management framework.
  Keywords: capability management; manufacturing research centres; valley of death; technology capabilities; maturity; readiness; people; equipment; project; framework.
  
  
• A Comprehensive Study of Identification of Microstructural Analysis in Various Reinforced Fly Ash Concretes  
  by J. Mahesh 
  Abstract: This investigation reveals a critical experimental study in identifying the pictorial view of pore structure of concrete in different types of concretes comprising of Class-F fly ash together with reinforcement over dissimilar fine aggregates like manufactured and river sands. Moreover, this investigation reports the analysis over dissimilar water curing conditions in finding out the pictorial view of pore structure of the concrete. For this experimentation, cement was partially replaced using fly ash and concrete mixes that were formed with 40%, 30% and 20% weights of cement and by using 16 mm diameter reinforcement. The performance analysis of this experiment was done by using X-ray diffraction spectrometry (XRD) and Scanning electron microscopy (SEM). Moreover, this investigation recommends the use of concrete mix with 30% fly ash replacement in concrete.
  Keywords: Concrete; Curing; Fly ash; Manufactured sand; XRD; SEM; Microstructure.
  
  
• Agile approach as an answer to internal uncertainty: a case study in large scale manufacturing  
  by Abdulkadir Özgen, Mehmet Gençer 
  Abstract: The success of agile product development in the software industry has attracted the attention of the industrial new product development (NPD) community, and these approaches are suggested as an alternative NPD method in large-scale organizations. Agile approach to NPD has the potential to overcome the uncertainty that dominates today's business conditions. However, there is little research regarding the performance of this approach and its practices, most of which were developed in the software industry, in other contexts. In this paper, we report findings of a qualitative case study on agile NPD efforts in a large-scale manufacturing firm. In contrast to software development, NPD projects in this context span several organizational units and have high organizational complexity. Through a case study methodology, we explore how agile practices address organizational uncertainty. The study, based on semi-structured interviews, covers two NPD projects with a total of 12 sub-teams. Our results indicate that in a large organization, internal sources of NPD uncertainty dominate external sources. The three factors in organizational uncertainties are interdependency, team volatility, and global dispersion of teams. Furthermore, we develop a model to explain how various agile practices can provide the NPD teams with capabilities to mitigate these organizational uncertainties.
  Keywords: Agile Practices; New Product Development; Large-scale organizations; Uncertainity.
  
  
• Investigation on Impact Strength of 3D Printed PLA: Effect of Part Orientation, Infill Pattern and Infill Percentage  
  by Harshit Dave, Naushil Patadiya, Shilpesh Rajpurohit, Ashish Prajapati, Harit Raval 
  Abstract: Fused Deposition Modeling (FDM) is an extensively adapted 3D printing process owing to its ease of operation and low cost. In the present work, the FDM technique was used to examine effect of the processing parameters on the impact strength of FDM manufactured Polylactic Acid (PLA) material. Test specimens were printed while varying build parameters, including infill pattern, part orientation and infill density. The prepared parts were subjected to Izod impact test to determine the impact properties. It is observed that specimens printed in X orientation usually displayed better impact properties than the specimen oriented in the Z orientation. The rectilinear pattern and higher infill density displayed higher impact strength. Furthermore, SEM analysis on the specimen's fractured surface was done to evaluate the impact of build conditions on the failure mechanism of samples.
  Keywords: Fused deposition modeling; Impact strength; Part orientation; Infill pattern; Rectilinear; Concentric; Hilbert; Infill density.
  
  
• Price decision analysis for perishable products under threat of entry: The case of vertical product differentiation  
  by Hao Li, Yang Qian, Hao-nan Xu, Xiang Gao 
  Abstract: Perishable goods companies respond to competitive pressures through differentiated strategies, but pricing issues have become more complicated. This study analyses the optimal pricing of two companies offering vertically differentiated products to strategic customers who are intertemporal utility maximisers. It is assumed that incumbent companies respond to the entry threat of late-stage enterprises through pricing strategies. A two-period dynamic price game model is constructed under the price commitment and dynamic pricing strategies, and this problem is modelled based on the companys objective to maximise total expected profits and the optimal timing of the latecomers entry. It is demonstrated through numerical examples that the timing of a latecomer entering the market under commitment pricing is delayed with the increase in a customers strategic behaviour. It is also shown that an incumbent company adopting commitment pricing may have much higher profits than one that uses dynamic pricing. Interestingly, a lower customer pleasure level makes the incumbent companys revenue decline.
  Keywords: vertical product differentiation; price commitment; dynamic pricing; strategic consumer behaviour; optimal policy; revenue management; threat of entry; perishable goods; time to enter the market; psychological pleasure.
  
  
• PROCESS INNOVATION THE BLIND SPOT IN PRODUCT INNOVATION. DEVELOPMENT OF A GENERIC FRAMEWORK FOR THE FRONT-END IN PROCESS INNOVATION.  
  by Hubert Wittke, Alan Ryan, Ann Ledwith, Mark Southern 
  Abstract: This study aims to consolidate the fragmented knowledge dispersed across simple or incomplete (existing) frameworks on process innovation and identifies the research gaps in the management of the front-end stage. The outcomes contribute to the present knowledge by a comprehensive review (with the Systematic Literature Review methodology) and synthesis of twelve management frameworks of process innovation. The paper also presents a novel framework for management of the front-end of process innovation in manufacturing companies. This research identifies that the front-end in process innovation must integrate with activities linked to product innovation, if innovation projects are to be successful.
  Keywords: Process innovation; front-end; FFE; generic framework; product innovation; management; research gaps; systematic literature review; synthesis; manufacturing enterprises.
  
  
• Technological and organizational factors to succeed in Industry 4.0 transition implementation: an empirical study  
  by Valérie Rocchi, Daniel Brissaud, Arko Steinwender, Arnaud Bocquillon 
  Abstract: The Fourth industrial revolution and its disruptive ICT technologies for production systems are of crucial importance for the growth of European companies and especially SMEs. Nevertheless, few of them have reached the digital transformation with its expected performance yet. This paper aims at identifying the critical success factors that support a successful implementation of Factory of the Future practices. It relies on a qualitative survey addressed to 96 industrial companies that have already implemented Industry 4.0 technology and carried on in five Alpine Space countries. Five critical success factors have been identified and ranked on a Likert scale. From these ones, 24 guidelines have been designed for supporting the digital transition of industry. The results of the industry survey contribute to improve diagnosis and monitoring tools. This empirical study allows for going beyond the current industry 4.0 approaches and brings new tools for Factory of the Future implementation.
  Keywords: Industry 4.0; manufacturing; SMEs; critical success factors; industrial organisation; empirical study.
  
  
• An Optimization control method of manufacturing whole process based on real-time information drive  
  by Xiao-hua Qi, Guan-yi Wei 
  Abstract: In order to overcome the problems of low production efficiency and large deviation in production process tracking, this paper proposes a real-time information driven optimisation control method for the whole production process. Firstly, scan the manufacturing process through the physical unit of the whole manufacturing process. Secondly, the real-time information drive is used to design the information acquisition unit of the production line. Then, the real-time information flow drive of the production line is formed. Finally, the adaptive production and manufacturing parameters are calculated, and then combined with the firefly algorithm to complete the optimal control of the whole production and manufacturing process. The experimental results show that the enterprise output of this method is higher, and the tracking absolute value deviation does not exceed 0.01, indicating that the whole process optimisation control effect of this method is better.
  Keywords: information flow drive; real-time acquisition; production parameters; the whole process; firefly algorithm; optimal control.
  DOI: 10.1504/IJMTM.2022.10051232
   
  
• An Intelligent Buffer Capacity Allocation Method for Flexible Production Lines Based on Conjugate Bayes Estimation  
  by Jinrong Li  
  Abstract: In order to overcome the problems of low productivity, high vacancy rate and long allocation time in traditional methods, an intelligent buffer capacity allocation method based on conjugate Bayesian estimation is proposed in this paper. Firstly, the basic function of flexible production line is determined, and the relationship between steady performance parameters and buffer capacity is analysed. Secondly, Gershwin decomposition method is used to solve the performance parameters of flexible production line system. Then, the proper conjugate prior information is determined and the process distribution parameters are estimated using conjugate Bayes. Finally, the buffer capacity intelligent allocation value of flexible production line is calculated to realise buffer capacity intelligent allocation of flexible production line. The experimental results show that the proposed method can achieve 97.6% equipment productivity, 2.3% equipment vacancy rate and 6.6s allocation time, and has good buffer capacity allocation effect.
  Keywords: conjugate Bayesian estimation; flexible production line; prior information; buffer capacity; intelligent allocation of capacity.
  DOI: 10.1504/IJMTM.2022.10051233
   
  
• Dexterity control of multi-arm sorting robot based on machine learning  
  by Linyan Pan 
  Abstract: In order to overcome the problems of large dexterity control error of manipulator joint and poor sorting and positioning accuracy, this paper designs a dexterity control method of multi manipulator sorting robot based on machine learning. Firstly, the attitude of the multi manipulator coordinate system on the rigid body is obtained. Secondly, the translation matrix is constructed by using the translation transformation method. Then, the rotation matrix is constructed to determine the inverse motion law of the robot. Finally, determine the dexterity parameters of the manipulator joint, introduce the machine learning algorithm to calculate the dexterity parameter control error, and correct the error through the activation function to complete the dexterity control. The experimental results show that the error of this method is always less than 0.1% and the positioning accuracy is higher than 90%, which shows that the dexterity control effect of this method is good.
  Keywords: machine learning: multi-manipulator; robot; dexterity; translation transformation; rotation matrix; activation function.
  DOI: 10.1504/IJMTM.2022.10051411
   
  
• Fuzzy System for Image Defect Detection Based on Machine Vision  
  by Yiqiang Lai, Yongjun Qi, Xianfeng Zeng 
  Abstract: With the continuous upgrading of the industrial field, the market’s requirements for product quality are also increasing, which requires more accurate product monitoring equipment. This paper analyses the composition of the vision system, and compares the collected images with the defects under manual detection based on the non-local mean denoising algorithm, and the results meet the system requirements. The experimental results show that the image size is 140*141, and the distortion rate is 0.992; the image size is 120*81, and the distortion rate is 0.703. This means that the larger the image size, the higher the distortion. Before the improved algorithm, a total of 47 defects were detected, while after the improved algorithm, a total of 83 defects were detected. It can be seen that when the algorithm is improved, the number of defect detections increases significantly.
  Keywords: machine vision; image processing; image defect detection; fuzzy systems.
  DOI: 10.1504/IJMTM.2022.10051413
   
  
• Image Dehazing Network based on Improved Convolutional Neural Network  
  by Changxiu Dai  
  Abstract: Image dehazing enhances its quality by restoring the actual pixels influenced by poor light and intensity due to environmental and other factors. Hazy images are rectified to improve visibility, guidance, and object recognition through channel attribute corrections. This article introduces a pre-emptive dehazing network (PDN) using an improved convolutional neural network (ICNN) for single to multi-image dehazing. In the proposed method, neural network layers are operated for intensity-based single and multi-feature analysis. The image is split based on intensity pixels for identifying the channel corrections. This channel correction and intensity verifications are processed using CNN in different independent layers. In the CNN training, the channel correction from the hidden layers and pixel correlation from the external dataset is performed for dehazing the image pixels. The dehazed pixels are organised based on the original input organisation for verifying the similarity measure. The proposed method’s performance is validated utilising the metrics similarity, error, precision, F1-score, and time complexity.
  Keywords: channel correction; convolutional neural network; CNN; image dehazing; pixel correlation; pre-emptive dehazing network; PDN.
  DOI: 10.1504/IJMTM.2022.10051436
   
  
• Economic Investment Risk Prediction Model and Algorithm based on Data Mining Method  
  by Yi Chen  
  Abstract: Investment decisions have a broad and far-reaching impact on the operating conditions of the entire enterprise. Once the investment decision is wrong, it will bring huge risks. As a data analysis technology, data mining can simulate mathematical models or algorithms by analysing historical data, which greatly improves the accuracy of prediction. The purpose of this paper is to study the application of data mining technology in the field of investment management. This paper constructs an economic investment risk prediction model based on data mining. The research results show that the sensitive factor affecting the investment status in the model obtained by the data mining algorithm is the quick ratio. When the quick ratio is less than or equal to 1.603, the investment is one year; if the result is greater than 1.603, the investment is five years.
  Keywords: investment risk; data mining; cluster analysis; factor analysis; decision tree.
  DOI: 10.1504/IJMTM.2022.10051525
   
  
• Design of Computer Image Automatic Processing System Based on Artificial Intelligence Algorithm  
  by Guoqiang You  
  Abstract: Automatic image processing systems are applied for recognising human faces in crowds, person identification, and face matching applications. The varying textures, input representation, and position impact detection accuracy and recognition. Therefore, this article introduces an automatic image processing method (AIPM) for face recognition (FR) using deep learning (DL) paradigm. This method extracts the textural features based on the image position and classifies them based on pixel mapping. Semantic (even) and uneven pixel variations are observed in the classification process. The semantic classified pixels are used for correlating different image segments that are further used for training the learning network. The uneven pixels classified using DL is discarded to prevent recognition errors. The DL paradigm verifies the pixel position and coordinate mapping between different inputs. The detection is improved based on the classified output for semantic and uneven pixels. The training is based on semantic and mapping pixels, for which the training is improvised using erroneous pixels. Therefore, precision is improved with controlled analysis complexity.
  Keywords: artificial intelligence; automatic processing; face recognition; feature extraction; automatic image processing method; AIPM.
  DOI: 10.1504/IJMTM.2022.10052039
   
  
• Automatic Feature Based Inspection and Qualification for Additively Manufactured Parts with Critical Tolerances  
  by Christopher Kelly, Richard Wysk, Ola Harrysson, Russell King, Brandon McConnell 
  Abstract: This work expands the capabilities of the Digital Additive and Subtractive Hybrid (DASH) system by including "geometric qualification" of mechanical products. Specifically, this research incorporates the extended Additive Manufacturing Format files (AMF-TOL) which include American Society of Mechanical Engineers (ASME) Y14.5 specifications for planes, cylinders and other features so that "in-process" inspection can be completed automatically. An example for the production of hols is provided to illustrate On-Machine-Measurement collects sample radii to estimate the size and position of finished cylindrical features. Statistical analysis was used to measure bounds for comparison to specified tolerance callouts to determine whether a part is within specification, within a user-defined level of confidence. Seven different sampling strategies were evaluated on a DASH part including the bird cage sampling strategy defined in ISO-12180. Part data was utilized to show that for large data samples no statistically significant difference in accuracy was identified for four methods. Finally, analysis shows that using the DASH process with automatic inspection is economically advantageous for low volume production runs.
  Keywords: Additive manufacturing; CNC machining; Hybrid manufacturing; Inspection.
  
  
• Automatic Human Face Recognition System of Image Processing Based on BP Neural Network Paradigm  
  by Pei Yang, Guoqiang You 
  Abstract: Observation video analysis is useful in recognising human faces in crowded and coinciding scenarios. Overlapping images result in false recognition due to non-semantic textural features. The boundary analysis varies for this process, generating segments exceeding masks of the original image. Backpropagation learning (BPL) based textural-edge detection and recognition model (TED-RM) is designed to resolve this issue. The proposed model exploits the masked and un-masked textural features for identifying the semantics of the input. After this identification process, appropriate features are analysed for semantics and correlation with the inward and overlapping video image input edges. The masked and un-masked regions’ semantic features are recurrently correlated with the previous datasets for independent human faces. The mapping feature points are identified and correlated with the actual edge of the training input. The non-semantic edge points are classified for further training and validation to detect errors in further input analysis. The proposed TED-RM improves 10.84% high accuracy, 11.5% less processing time, 10.2% high true positives, 5.55% less error, and 10.6% high recall compared to existing methods.
  Keywords: DRL; face recognition; image semantics; texture classification; video analytics.
  DOI: 10.1504/IJMTM.2022.10055027
   
  
• Collaborative robots in small and medium-sized enterprises: a field-based feasibility model  
  by Marcos Vido, Salvatore Digiesi, Francesco Facchini, Wagner Lucato 
  Abstract: The Industry 4.0 revolution has led to new concepts and transformations toward technological innovations. In the manufacturing sector, the use of collaborative robots has significantly increased in the last few years, enabling them to work safely alongside humans in a shared workspace. Within this perspective, small- and medium-sized enterprises (SMEs) have been facing several challenges compared to large organizations regarding the adoption of collaborative robots. Based on the literature, this paper aims to introduce a techno-economic feasibility model to evaluate the viability of using collaborative robots in a shared workplace, with a focus on SMEs. Consistent with the paper's aim, a conceptual model was developed, supported by experts' opinions using the Delphi method. The results of this work incorporate contributions to both the academic and industrial communities.
  Keywords: collaborative robot; SMEs; feasibility analysis; industry 4.0.
  
  
• Simulation of EPC Consortium Partnership Stability and Data Based on Prospect Theory  
  by Judan Hu, Shuang Tang, Minjie Yang 
  Abstract: For the rapid promotion and healthy development of the EPC general contracting mode, this paper constructs a game model for the stability evolution of the EPC consortium tripartite cooperation relationship based on the prospect theory from the perspective of the EPC consortium led by the design unit, analyses the behavioural interaction mechanism of the game subjects and the factors affecting the system evolution, and uses system dynamics for data simulation. The results show that the rate at which the EPC consortium triad eventually evolves into a stable cooperation strategy is positively related to the initial probability, loss avoidance coefficient, gain sensitivity, and gain/loss sharing coefficient, and negatively related to the risk pursuit coefficient. The steady state of the system is influenced by the strength of penalty and the level of regulation/cooperation cost. This paper can provide insights and a theoretical basis for the long-term stable development of EPC consortium.
  Keywords: EPC consortium; cooperative stability; evolutionary games; prospect theory; system dynamics.
  DOI: 10.1504/IJMTM.2023.10056209
   
  

Special Issue on: LISS16-OPMSC Optimisation Problems in Manufacturing and Supply Chains

• CORRELATION ANALYSIS AND PRIORITIZED ABC FSN MATRIX FOR PHARMACY INVENTORY MANAGEMENT  
  by Manivel Palanisamy 
  Abstract: Objective The aim of the study was to identify the pitfalls in the existing supply chain of private and hospital pharmacies, identify the variables that influencing more in the efficiency of the pharmacy, select the appropriate inventory analysis and suggest the prioritized inventory matrix to meet customer requirement in efficient manner. Methods The qualitative and quantitative data has been collected through questionnaire and interview of the pharmacy personnel. Through SPSS, the normal distribution and correlation analysis to be carried out on sample data. The pitfalls were solved by the selection of appropriate inventory analysis and suggesting the prioritized inventory matrix to narrowed down the drugs for monitoring and control strategies of pharmacy drugs. Results The normal distribution and correlation analysis results shows that the variables collected through questionnaire are normally distributed and the variables that most influence the efficiency of the pharmacy supply chain. The implementation of Prioritized ABC FSN matrix in pharmacy will helps to provide high-quality service to the customer and there will be an adequate supply of the items in the pharmacies. The future work also to be discussed. Conclusion The prioritized ABC FSN matrix to be adopted as a routine practice for optimal use of resources and elimination of out-of-stock and over stock situations in the hospital and private pharmacy.
  Keywords: Pharmacy Supply Chain; Inventory Management System; Stock Outs; Overstock; IT Support in Pharmacy; correlation analysis; Inventory analysis.
  
  

Special Issue on: Big Data and AI for Process Innovation in the Industry 4.0 Era

• Research on total amount prediction of import and export trade data based on combined predicting model  
  by Jianxin Chen, Xiaoke Zhao 
  Abstract: In order to overcome the problems of low index significance, low prediction efficiency and low prediction accuracy in the process of prediction of import and export trade data, a new research method for total amount prediction of import and export trade data based on combined prediction model. Combine neural network prediction method and support vector machine prediction method to build a combined prediction model. Through the back propagation process, it can reduce the error between the expected and the actual output, and modify the network threshold and weight, so as to realize the classification of samples in high-dimensional space in support vector machine, and the two methods are combined to complete the prediction of total import and export trade data. The experimental results show that the significance of the proposed method is close to 100%, the prediction time is within 0.5 min, and the prediction accuracy is more than 90%.
  Keywords: Combination predicting model; Import and export trade; Data predicting; Influencing factors.
  
  

Special Issue on: The Design and Management of Serviceability Products and Systems, Smart Industrial and Manufacturing Systems

• Measurement of Suction Cups Release Time for Press Line  
  by Xiaowan Zheng, Bicheng Guo, Boyang Zhang, Siyuan Fang, Bernard Sia, Lianxiang Yang 
  Abstract: Suction cups are widely used in press lines to handle and transfer sheet metal. The release time, which directly affects production efficiency and safety, refers to the dropping off period in which the product completely separates from the suction cups. As of now, no release time data is currently available for use in evaluating press line. To provide such data, an experimental setup has been developed. The setup includes vacuum and non-vacuum system designed to simulate the release process of the press line and an electronic triggering system calculating the release time based on controlling the load. The four most commonly used suction cups, namely the large (110 mm diameter) double and single layer suction cups and small (60 mm diameter) double and single layer suction cups, were tested using the setup. The results show that the measurement system is practical and will provide important information for press line optimization.
  Keywords: Suction cup; release Time; press line; sheet metal gripping; sheet metal transferring; Electronic Measurement System.
  
  
• An integrated storage method of industrial 4.0 processing data based on big data mining  
  by Xiaoyuan Luo, Jun Liu 
  Abstract: In order to overcome the problems of poor integration integrity and low storage security of traditional industrial processing data integrated storage methods, a new industrial 4.0 processing data integrated storage method based on big data mining is proposed in this paper. Firstly, the hierarchical clustering method in big data mining is used to mine processing data from industrial 4.0 data. Secondly, based on the mined processing data, the clustering attributes of different processing data are calculated to integrate clusters. Finally, Bayesian method is used to complete the integrated storage of industrial 4.0 processing data. The experimental results show that compared with the traditional integrated storage methods, the integration integrity and storage security of this method are significantly improved, and the maximum integration integrity can reach 97%.
  Keywords: Big data mining; Industry 4.0; Processing data; Integrated storage.
  
  
• Calibration method of mechanical accuracy of drug dissolution meter based on Wavelet Transform  
  by Baihu Sun, Bo Yang, Liyuan Zhang 
  Abstract: Aiming at the problems of large mechanical accuracy calibration error in the existing mechanical accuracy calibration methods of drug dissolution meter, a mechanical accuracy calibration method of drug dissolution meter based on wavelet transform is proposed. Firstly, the internal structure and operation process of the drug dissolution meter were analyzed to determine the key parameters; Then, the weight of key parameters is determined by entropy, and the parameters with higher weight are used as the calibration object; Finally, with the help of wavelet transform wavelet signal decomposition and reconstruction, the mechanical accuracy calibration model of drug dissolution instrument is constructed, the mechanical operation parameters of drug dissolution instrument are taken as the model input data, and the mechanical accuracy calibration results of drug dissolution instrument are corrected by singular value packet decomposition. The results show that the calibration error of the proposed method is less than 5%.
  Keywords: Wavelet transform; Drug dissolution meter; Mechanical accuracy; Calibration; Singular value packet decomposition; Decomposition and reconstruction.
  
  
• Full compensation method of thermal error of NC machine tool based on sequence depth learning  
  by MingXun Zhu, Zhigang Meng 
  Abstract: In this paper, a full compensation method of thermal error of NC machine tools based on sequence depth learning is proposed. Firstly, the main structure of NC machine tool is analyzed and the principle of thermal error compensation is determined; Then, multiple temperature test points are set at the machine body and main shaft to collect thermal error data. Secondly, the correlation degree of thermal error difference sequence is determined according to the running space state. Finally, the thermal error full compensation model is constructed with the help of RNN network algorithm in sequence depth learning, and the model is modified with the help of Lagrange function to realize full compensation. The results show that the total compensation error of thermal error of NC machine tool is less than 2%.
  Keywords: Cequence depth learning; Compensation effect; Numerical control machine; Thermal error; Full compensation.
  
  
• A Fuzzy PID control method of step response of torque hydraulic mechanical transmission  
  by Yingjian Deng 
  Abstract: In order to overcome the problems of large transmission speed calculation accuracy and control error existing in the traditional transmission step response control method, a new convergent torque hydro mechanical transmission step response fuzzy PID control method is proposed in this paper. According to the relationship between speed and torque of each component, the torque convergence compensation equation of hydro mechanical transmission is constructed. According to the transmission compensation results, combined with the fuzzy PID control principle, the fuzzy reasoning algorithm is used to modify the fuzzy control parameters, so as to obtain the improved fuzzy control equation and complete the step response fuzzy PID control of torque hydraulic mechanical transmission. The experimental results show that this method can accurately calculate the transmission speed of torque hydraulic machinery, and has lower control error, and the average control error is only 0.033.
  Keywords: Torque hydraulic machinery; Transmission step response; Fuzzy PID control; Fuzzy inference algorithm.
  
  
• Intelligent color selection method for product packaging design based on particle swarm optimization  
  by Jin Fan 
  Abstract: In order to solve the problems of poor correlation between image and color matching and low user satisfaction in the traditional color selection method of packaging design, a new color intelligent selection method of product packaging design based on particle swarm optimization algorithm is proposed in this paper. The color intelligent selection parameters are calculated according to the hue value, the optimization objective function of color intelligent selection parameters is constructed, the parameter optimization problem is transformed into the objective function solution problem, and the particle swarm optimization algorithm is used to solve the objective function to complete the parameter optimization. Combined with the image color enhancement algorithm, adjust the image brightness, enhance the image detail contour, and complete the intelligent selection of color. The experimental results show that this method is feasible and user satisfaction is high in color intelligent selection of product packaging design.
  Keywords: Particle swarm optimization; Product packaging design; Intelligent color selection; Image enhancement; color matching.
  
  
• Life-cycle cost assessment method for industrial products based on fuzzy fault tree  
  by Ming-hui Yuan, Yong-feng Wu 
  Abstract: In this paper, a fuzzy fault tree based evaluation method for industrial product life cycle cost was proposed. Determine the key index of the whole life cycle cost of industrial products, calculate the influence degree of cost index through the judgment matrix, and determine the weight of cost index. The least square method is used to extract the least square components of key costs and construct the life cycle cost evaluation model of industrial products. The evaluation results were sorted by fuzzy number, and the failure rate of the fuzzy number after sorting was calculated. The occurrence probability of the optimal value in the evaluation model was determined by fuzzy fault tree top events, and the optimal value of the model was solved. Experimental results show that the accuracy of the proposed method is always higher than 90%.
  Keywords: Fuzzy fault tree; key index; least square method; top event; fuzzy number inefficiency.
  
  
• An optimization method of factory terminal logistics distribution route based on K-means clustering  
  by Hui Zhang 
  Abstract: Aiming at the problems of scattered logistics data and low logistics distribution efficiency in the existing factory end logistics distribution route planning methods, a factory end logistics distribution route optimization method based on K-means clustering is proposed. Firstly, information entropy is introduced to optimize the classical K-means dynamic clustering algorithm to collect the factory end logistics distribution data; Then, a priori clustering insertion algorithm is used to process the redundant data in the collected logistics distribution data. The priority characteristics of logistics distribution nodes and the subset of distribution service requirements are established, and the end distribution route planning process is designed. Finally, by setting the starting point of collection and distribution route through the process, determine the data weight in the distribution data set, the optimal route of factory end logistics distribution to realize optimization. The results show that this method has low cost and time-consuming less than 0.3h.
  Keywords: K-means clustering algorithm; Factory end logistics; Logistics distribution route; Location of distribution Center.
  
  
• An enterprise logistics cost management method under the trend of industry 4.0  
  by Guomeng Zhao 
  Abstract: In order to overcome the low accuracy of cost factor and total cost calculation in traditional logistics cost management methods, this paper proposes a method of enterprise logistics cost management based on factor weight under the trend of industry 4.0. Firstly, the paper analyzes the transportation mode of enterprise intelligent logistics under industry 4.0, and defines each link of intelligent logistics. Secondly, according to the transportation characteristics of smart logistics, the logistics cost factor is obtained and the weight of logistics cost factor is calculated. According to the weight calculation results of logistics cost factors, the total logistics cost is calculated. Finally, build Likert scale, judge the level of logistics cost, complete the enterprise logistics cost management. The experimental results show that this method can accurately calculate the weight of logistics cost factors and the total logistics cost, and it is more reasonable for enterprise logistics cost management.
  Keywords: Industry 4.0 trend; Enterprise logistics cost; Cost control.
  
  

Special Issue on: Smart Production and Logistics Within an Industry 4.0 Environment

• Exploring the knowledge domain and future research directions in Industry 4.0 for small and medium enterprises: A scientometric analysis  
  by Reza Shamseddini, Moslem Alimohammadlou, Habib-Allah Ranaei Kordshouli, Mohammad Hossein Ronaghi 
  Abstract: Industry 4.0 represents a new manufacturing paradigm in which there is a convergence between progressive information technologies and manufacturing technologies. As such, Industry 4.0 can create good opportunities for small and medium enterprises (SMEs). The purpose of this study is to investigate the current status and the future directions of research concerned with Industry 4.0 for SMEs. To accomplish this, the study conducts a scientometric analysis of the records indexed on the Web of Science database to identify the research frontiers, current hot topics, and future directions of studies exploring Industry 4.0 for SMEs. The analysis is processed in CiteSpace software. The findings show that Industry 4.0 has a significant function in transforming SMEs manufacturing and business models. Also, the result of this study can help future studies to have an insight into the frontiers of research exploring Industry 4.0 for SMEs and to clearly choose their research directions
  Keywords: Industry 4.0; SMEs; scientometric.
  
  
• Managing the Life Cycle Assessment for high-performance refrigerators through a comparative analysis of the impacts  
  by Rosa Francesca De Masi, Marialuisa Menanno, Silvia Ruggiero, Giuseppe Peter Vanoli, Matteo Mario Savino 
  Abstract: Today the continuous improvement of refrigeration systems is a topic of discussion both for energy and for environmental sector. The purpose of this work is to develop a research methodology to compare the environmental impacts of two industrial refrigerators through Life Cycle Assessment (LCA). The research was stimulated by the need to identify technology solutions that allows high performances, low energy consumption and low environmental impact. Within the study, trough LCA we appraise the impacts long by the whole lifecycle - from cradle to grave - of two typologies of industrial refrigerator having different insulations technologies. Then, we develop a comparative analysis through different LCA assessment methods between two models having different insulations technologies. Among the main results, the analysis shows that the insulating material does not have high environmental impact, while the highest impact is due to internal and external transports.
  Keywords: Product Development; LCA analysis; Industrial refrigeration; Environmental impact.
  
  
• Effect of Submerged Arc Welding Process on Hardness and impact Properties of Fabricated SAE1020 Low carbon Steel Plates.  
  by MANNE KAUSHIK, ABID MUSA MULLA, Nikhil PrakashRAUT 
  Abstract: This Paper Studies the effects of Submerged Arc Welding(SAW) on impact and Hardness Properties of the low Carbon Steel Plates inline with SAE1020 grade.The Test Specimen of low Carbon Steel Plates with 10mm thickness used as base material for Preparing joint using Submerged arc Welding.The impact and Hardness Properties are investigated using Charpy impact Testing Machine and Brinells Hardness Testing Machine.The results obtained for testing Shows that welded joint of low Carbon Steel Plate have Superior Hardness and impact Strength than the other methods.The reason for better mechanical Properties is due to the Presence of finer grains in heat affected Zone and fusion Zone.welding test Samples were tested by varying the three Process Parameters like Welding Voltage,Current,Travel Speed and Fluxes
  Keywords: Low Carbon Steel Plate,Submerged Arc Welding,Charpy Impact Test,Hardness Test.
  DOI: 10.1504/IJMTM.2022.10052690
   
  
• Challenges and expectations about 5G in the industry: evidence from survey-based research  
  by Chiara Cimini, Fabiana Pirola, Sergio Cavalieri 
  Abstract: The introduction of the fifth generation of Mobile Wireless Communication, the 5G, is expected to have disruptive impacts on the manufacturing and logistics processes. The possibility to ensure smarter and faster mobile communications supports applications in several fields, from factory automation to maintenance, quality and logistics, enhancing the adoption of augmented and virtual reality, cloud robotics and artificial intelligence. The aim of this paper is to present an overview of the 5G characteristics and applications in the industry. Moreover, this paper reports the results of a survey conducted in Italian companies, investigating the current level of knowledge and expectation about 5G adoption. The results show an interesting perspective about the barriers that currently create a gap between the high-perceived importance and the current low level of 5G implementation in industry, demonstrating how, despite relevant benefits are expected, companies still have a prudent attitude in addressing investment in 5G.
  Keywords: 5G; Mobile Wireless Communication; Smart Manufacturing; Survey.
  
  
• The Fourth Industrial Revolution: Mapping the future  
  by Zahra Khoshsepehr, Maslem Alimohammadlou, Ali Mohammadi, Habib-Allah Ranaei Kordshouli 
  Abstract: Scholars view Industry 4.0 as a set of emerging technologies that provides a novel approach to technology. Industry 4.0 is a revolution that has arisen from transformations in the physical, digital, and biological aspects of human life. This revolution occurred with the advent of smart sensors, artificial intelligence, machine learning, and cyber-physical systems. Smart technologies have a critical role in Industry 4.0, although previous research has not extensively explored the changes such technologies could bring about or future directions in research on Industry 4.0. The purpose of this study was to conduct a systematic review of Industry 4.0 emerging technologies and the ways they could affect future research directions. To accomplish this, all of the articles addressing Industry 4.0 were extracted from the Web of Science Core Collection (WoSCC) and were analyzed in CiteSpace. The results revealed that although Industry 4.0 emerged from developed countries (e.g., Germany), developing countries such as India focused on smart technologies more and could achieve a considerable industrial status in the near future. Meanwhile, such countries as Germany and China tried to hugely expand their research collaborations with other countries. The findings also clarified that although research on Industry 4.0 previously focused on engineering, over the past years studies in this field mostly investigated such topics as the environment, management, quality, and Society 5.0, which could shape the future research directions of Industry 4.0. The novelty of this research consisted in its categorization of the studies from various perspectives, co-citation analysis findings, and a clear mapping of future research trends based on the current status. The findings could help researchers gain insights into the frontiers of research exploring Industry 4.0 and obtain valuable information contributing to the development of future research directions in this field.
  Keywords: Industry 4.0; Co-cited analysis; Research collaboration; Burst detection.
  
  
• DESIGN AND EVALUATION OF NEW MANUFACTURING PROCESS FOR BLOOSTER PIN  
  by MANISH DESHMUKH, Anshul Gangele, Deepak Kumar Gope 
  Abstract: Blooster pins or bell crank pins are used to hold the bell crank lever, in the gear box of automobiles, which alter the movement through 90° or 180°. This paper lays a revised design for manufacturing (DFM) plan for the production of the blooster pins, which is validated by using the MSA and Statistical quality control techniques to evaluate the process performance. In order to reduce the failure risk, a new control plan as well as process failure mode and effect analysis (PFMEA) plan has been devised. The %gauge repeatability and reproducibility (GRR) of the measuring system for the new DFM process has been evaluated to be 21.20% implying the acceptability of the existing system for measurements of the new design and the process capability indexes have been calculated to be 1.39 and 0.85 respectively, which indicates the proposed DFM process of the blooster pin is has good capability.
  Keywords: bell crank pin; design for manufacturing; DFM; MSA; SPC; gauge repeatability and reproducibility; GRR; process capability index.
  
  

Special Issue on: Smart Manufacturing Systems for Industry 5.0 Challenges and Opportunities

• A path planning algorithm of intelligent transportation robot based on extended Kalman filter  
  by Guan He, HongLan Yang 
  Abstract: Aiming at the problem of long calculation time and slow response speed of traditional intelligent transportation robot path planning algorithm, an intelligent transportation robot path planning algorithm based on extended Kalman filter is proposed. By analyzing the relevant principles of optical flow localization, aiming at the fact that a single optical flow sensor can not meet the needs of all application scenarios, multiple optical flow sensors are fused through extended Kalman filter, and the system model and observation model of intelligent transportation robot are established at the same time. The optical flow sensor is fixed on the intelligent transportation robot, the two-dimensional coordinates of the intelligent transportation robot are obtained in real time, and the moving path is planned. The results show that the proposed algorithm can reduce the operation time and improve the response efficiency.
  Keywords: Extended Kalman filter; Intelligent transportation robot; Path planning algorithm; Observation model.
  
  
• Research on remote monitoring method of mechanical equipment fault based on virtual reality technology  
  by Yanmei Jiao, Huihui  Tian 
  Abstract: Aiming at the problems of poor fault monitoring effect, low precision and long time in the current mechanical equipment fault remote monitoring method, a mechanical equipment fault remote monitoring method based on virtual reality technology is proposed. Using virtual reality technology, build a three-dimensional model of mechanical equipment, analyze the operation status and perceived information of mechanical equipment, express the mechanical equipment fault in virtual reality, and realize the remote monitoring of mechanical equipment fault. The experimental results show that the average mechanical equipment fault identification ability of the proposed method is 97.8%, and the average mechanical equipment fault false alarm rate is 4.8%. When the mechanical equipment fault characteristic samples are 500, the mechanical equipment fault remote monitoring time is only 9.5s, the monitoring time is fast, the remote monitoring effect is good, and the monitoring accuracy is high; It has good application effect.
  Keywords: virtual reality technology; mechanical equipment failure; fault remote monitoring; three-dimensional model geometric transformation; FMECA; FTA;.
  
  
• An Adaptive Compensation Control Method for the Transmission Error of the Mechanical System Based on the Characteristic Model  
  by Wanwan Ren, You Wu, Ronghua Du 
  Abstract: Applying the characteristic model-based golden section adaptive (GSA) control theory, an adaptive error compensation control method for the transmission error of the mechanical system is proposed in this paper. A mechanical transmission system with a compensation mechanism was established, taking the ball screw as the main transmission component. The dynamics characteristic of the mechanical transmission system is analyzed. The GSA control theory based on the characteristic model is introduced. For the established characteristic model of the transmission system, the projection gradient method is used to identify its characteristic parameters online. The stability analysis of the closed-loop system consisting of characteristic model and GSA controller is carried out. The experimental results show that the characteristic model-based GSA control has a good effect on the transmission error compensation, as well as simple on-site debugging. The effectiveness and superiority of the method are verified.
  Keywords: Characteristic model ? Golden section adaptive control ? Feed transmission system ? Error compensation.
  
  
• Traceability Method of industrial product logistics information based on RFID Middleware  
  by Qingsong Zhang 
  Abstract: In order to improve the effect of logistics information traceability, this paper designs an industrial product logistics information traceability method based on RFID middleware. Firstly, RFID module is constructed and connected with SSH architecture to monitor the logistics transportation process in real time by using GPS technology. Based on this, the fractal box dimension of the location range of RFID middleware is determined to form a location update strategy. Finally, the logistics location traceability candidate area is constructed, and then the RF card location estimation method is constructed through probability statistics, taking the path with the largest probability value as the traceability path. The experimental results show that the average traceability success rate of this method is 93.54%, the location information acquisition time is less than 1.50 min, and the logistics location information matching accuracy can reach 95.1%, indicating that this method realizes the design expectation.
  Keywords: RFID middleware; Radio frequency identification; Logistics positioning; Location update; Traceability path.
  
  
• Frequency control method of cutting machining based on Wavelet Transform  
  by Chunling Li 
  Abstract: Because the traditional method does not effectively process the machining signal in the machining frequency control, there are some problems such as low control accuracy and unstable machining signal. Therefore, a frequency control method of cutting machining based on wavelet transform is proposed. The regulator command signal is used to adjust the phase of the speed regulation controller of the cutting machinery to realize the correction of the mechanical operation signal. The Lagrange method is used to estimate the mechanical vibration state, and the Fourier transform method is used to change the signal. It is concluded that the signal is relatively stable in the period of 0.43-0.75s. The method of wavelet transform is used to control the cutting machining frequency to realize the cutting machining frequency control. The experimental results show that this method has high control accuracy, can effectively remove machining noise, and has high application value.
  Keywords: Wavelet transform; Cutting machinery; Processing frequency; Speed controller; Virtual instrument; Fourier transform.
  
  
• Numerical simulation of combustion temperature field in circulating fluidized bed boiler  
  by XiaoFang Wu, LiFeng Zhang 
  Abstract: In view of the low accuracy and long simulation time of traditional methods in the numerical simulation of combustion temperature field of circulating fluidized bed boiler, a new numerical simulation and analysis method of combustion temperature field of circulating fluidized bed boiler is proposed. The combustion mathematical model of circulating fluidized bed boiler is constructed through gas phase combustion model, volatile component analysis model, coke combustion model and radiation model. On this basis, the physical model is established by gambit, and the grid is divided into blocks. The furnace is divided into several parts. Under the inlet boundary conditions, outlet boundary conditions and wall boundary conditions, the temperature field of circulating fluidized bed boiler combustion is numerically simulated. The simulation results show that the proposed method has high accuracy and short simulation time.
  Keywords: Circulating fluidized bed; Boiler combustion; Temperature field; Numerical simulation; Coke combustion model.
  
  
• Research on resource allocation management of industrial supply chain based on blockchain  
  by Yulong Wan, Xiaoying Bai 
  Abstract: In order to improve the efficiency and effect of industrial supply chain resource allocation, this paper studies the resource allocation method of industrial supply chain based on block chain. This method analyzes the coupling relationship between block chain and supply chain resource allocation management, updates the industrial supply chain resource pheromone, constructs the industrial supply chain resource allocation model through block chain technology, and realizes the industrial supply chain resource allocation management by combining the optimized simulated annealing algorithm. The experimental results show that the cost consumption rate of the proposed method is only 32.5%, the reliability is as high as 95.2%, and the configuration time is only 17.8s. Therefore, the proposed method has good resource allocation effect and improves the configuration efficiency.
  Keywords: blockchain technology; simulated annealing algorithm; industrial supply chain; supply chain resources; resource allocation model;.
  
  
• A Performance Evaluation of Supply Chain Management Based on Factor Clustering Analysis  
  by Yehui Dong, Jiawei Gao, Shanyin Yao 
  Abstract: In order to overcome the problems of low significance coefficient and low evaluation accuracy of current methods, a performance evaluation method of supply chain management based on factor clustering analysis was proposed. Firstly, SPSS software is used to standardize the data of influencing factors of supply chain management performance, and the factors that are not suitable for factor molecules are removed. Then, a factor analysis model was built, and the evaluated eigenvalue, eigenvalue contribution and cumulative contribution after model rotation were calculated. The clustering analysis of multiple common factors and the distance between samples were combined with the contribution calculation results. Finally, the correlation between supply chain management performance evaluation indicators is analyzed, the weight of evaluation indicators is calculated, and the performance evaluation results are obtained. Experimental results show that the significance coefficient of the proposed method is always higher than 0.8, and the accuracy is up to 98%.
  Keywords: Factor analysis; Cluster analysis; Supply chain management; Performance appraisal.
  
  
• Vibration fault detection method of boiler feed pump based on Hilbert vibration decomposition  
  by YanYuan Li, XingMing Zhao, ZhongZhu Liu, XiaoFang Sun 
  Abstract: In this paper, a vibration fault detection method of boiler feed pump based on Hilbert vibration decomposition is proposed. Firstly, the vibration signal characteristics of boiler feed pump are analyzed; Then, the wavelet threshold denoising principle is used to quantify the vibration signal and obtain the denoised vibration signal; Then, Hilbert vibration decomposition method is used to decompose the vibration signal and extract the signal features; Finally, the fault type of the feed water pump is judged by the abnormal increase of the feed water pump outlet pressure and the failure of the full opening of the deaerator. The simulation results show that the accuracy of vibration fault detection of boiler feed pump by the proposed method is up to 100%, and the detection time is within 18.32s. The detection accuracy of the proposed method is high and the detection time is short.
  Keywords: Hilbert vibration decomposition; Boiler feed pump; Fault detection; Wavelet threshold.
  
  
• Adaptive scheduling of agricultural machinery equipment production lines for intelligent manufacturing  
  by Jian Yan 
  Abstract: Aiming at the problems of low utilization, low balance and long time of traditional scheduling methods, an adaptive scheduling method of agricultural machinery equipment production lines for intelligent manufacturing is proposed. Firstly, according to the number of production plans and the fixed position of the production line, the adaptive scheduling mathematical model of the production line is established. Then, Gaussian mutation operation is used to mutate the pheromone of ant colony algorithm to complete the improvement of ant colony algorithm. Finally, the improved ant colony algorithm is used to solve the production line adaptive scheduling model to realize the adaptive scheduling of agricultural machinery equipment production line. The experimental results show that the average utilization rate of this method is as high as 94.8%, the average equilibrium degree is as high as 94.4%, and the scheduling time is only 15.9s.
  Keywords: intelligent manufacturing; improved ant colony algorithm; agricultural machinery equipment; production line scheduling; adaptive scheduling model;.
  
  
• Construction of human resource allocation model of flow production line based on Fuzzy Mathematics  
  by Chengye Zhang 
  Abstract: In order to improve the rationality and access rate of human resource allocation, a method of constructing human resource allocation model of assembly line based on fuzzy mathematics is proposed. Firstly, human resource data is encrypted through chaotic sequence. Then, the talent flow of assembly line is regarded as a random variable, and a Markov prediction model is established to reduce the prediction error combined with constraints. Finally, the fuzzy mathematical algorithm is introduced to divide the importance degree of posts, establish the human resource allocation model, and realize the human resource allocation of assembly line. Verification shows that the maximum matching degree of the method is 1.90, and the access rate is less than 2s, which effectively improves the matching degree and reduces the access time.
  Keywords: Fuzzy mathematics; Human resource allocation; Prediction model; Chaotic sequence; Markov;.
  
  
• An evaluation model of manufacturing innovation ability based on factor analysis method  
  by Jinping Qiu 
  Abstract: In order to overcome the problem of poor accuracy of innovation capability evaluation model, this paper proposes a manufacturing innovation capability evaluation model based on factor analysis.Firstly, build the evaluation index system of manufacturing innovation ability. Secondly, the extension analytic hierarchy process is used to obtain the evaluation index weight of innovation ability.Finally, the data variables are selected to construct the sample matrix, the original data are standardized, transformed and tested according to the KMO test standard, the evaluation of manufacturing innovation ability is realized by calculating the factor score, and the evaluation model of manufacturing innovation ability is constructed based on the factor analysis method.The experimental results show that the evaluation time of innovation ability of this model is only 8.6s; The accuracy of the evaluation model in this paper is 99%, which shows that the reliability evaluation result of the model is better.
  Keywords: factor analysis method; extension analytic hierarchy process; manufacturing industry; innovation ability evaluation model.
  
  
• Classification and recognition method of intelligent storage goods based on visual servo  
  by Jinbin Zhao, Liyu Ma, Fei Gao, Shujian Chen 
  Abstract: This paper proposes an intelligent storage goods classification and recognition method based on visual servo.The camera coordinates are calibrated based on the visual servo system, and the quaternion Gabor filter convolution algorithm is used to extract the characteristic area of intelligent storage goods; The case differentiation algorithm is used to realize the characteristic area classification of intelligent storage goods; The visual servo technology is used to obtain the objective constraints of the intelligent storage goods recognition function, and the greedy heuristic algorithm is used to solve the optimal intelligent storage goods recognition function to realize the intelligent storage goods classification and recognition.The experimental results show that the classification and recognition accuracy of intelligent storage goods can reach 96.3, the classification and recognition accuracy can reach 97.2%, and the efficiency is significantly improved.
  Keywords: visual servoing; quaternion Gabor filter convolution algorithm; greedy heuristic algorithm; intelligent storage; cargo classification and recognition;rn.
  
  

Special Issue on: Advanced Manufacturing Technologies Development and Prospect

• Path planning method of industrial intelligent welding robot based on cuckoo search algorithm  
  by Shuangling Wang, Huige Chen 
  Abstract: In order to overcome the problems of large time cost and low planning accuracy of traditional path planning methods, a path planning method of industrial intelligent welding robot based on cuckoo search algorithm is designed. Firstly, the coordinate system of industrial intelligent welding robot motion and the kinematic model of industrial intelligent welding robot are constructed by using D-H parameter method. Then, set the non collinear points in the running space of the welding robot, calculate the running radius of the welding robot according to the determined center of the circle, and complete the obstacle location. Finally, the limited conditions of welding path planning of welding robot are set, and the cuckoo search algorithm is used to optimize the optimal welding path of robot. The experimental results show that the proposed method can effectively improve the efficiency and accuracy of path planning of industrial intelligent welding robot.
  Keywords: Cuckoo search algorithm; Industrial intelligent welding robot; Route planning; D-H parameter method;.
  
  
• Path coordination scheduling method of handling robot considering three-dimensional cargo space of intelligent warehouse  
  by Wang Cheng 
  Abstract: In order to optimize the path scheduling of the transport robot, shorten the operation time and improve the operation efficiency, a path coordination and scheduling method for the transport robot considering three-dimensional goods is proposed. Firstly, a transport robot path coordination scheduling model considering three-dimensional storage is constructed, and then the improved gray wolf optimization algorithm is used to solve the path coordination scheduling model, so as to obtain the optimal operation path of the transport robot considering the three-dimensional storage space of the smart warehouse. It is verified by experiments that this method has a good scheduling effect when considering the operation path of the three-dimensional cargo space handling robot in the smart warehouse. When transporting 500m~2500m goods, the time can be shortened by 5~13min, and the working efficiency of the handling robot can be improved.
  Keywords: Intelligent warehouse; Three dimensional cargo space; Carry; Robot; Path; Coordinated scheduling.
  
  
• The dynamic multi project human resource allocation method of manufacturing industry based on multidimensional model  
  by Yi Zhou 
  Abstract: In order to overcome the problems of low allocation accuracy and long allocation time, this paper designs a dynamic multi project human resource allocation method in manufacturing industry based on multidimensional model.Determine the total number of talents, workload and utilization efficiency, build a fuzzy set of human resources indicators, and calculate the different hierarchical weights of each indicator; The fuzzy comprehensive evaluation method is used to construct the index comprehensive evaluation matrix, the PCA interval model in the multi-dimensional model is used to orthogonalize each index, and the multilateral convex set model in the model is used to realize the intersection of index parameters in different regions, so as to realize the rational allocation of human resources.The experimental results show that the proposed method improves the accuracy of dynamic multi project human resources allocation in manufacturing industry, and the allocation time is short.
  Keywords: Multidimensional model; PCA interval model; Human resource allocation; fuzzy sets.