Template-Type: ReDIF-Article 1.0 Author-Name: Daibing Cheng Author-X-Name-First: Daibing Author-X-Name-Last: Cheng Author-Name: Zhongyan Luo Author-X-Name-First: Zhongyan Author-X-Name-Last: Luo Author-Name: Rong Ju Author-X-Name-First: Rong Author-X-Name-Last: Ju Author-Name: Yong Zhang Author-X-Name-First: Yong Author-X-Name-Last: Zhang Title: Pre-settlement audit in project cost management based on cloud computing Abstract: This research mainly analysed the audit method of pre-settlement in project cost management, which served as a reference for the work in this field. The basis of the pre-settlement audit was the specific information of construction material submitted by the construction party to ensure its authenticity and legitimacy, so that the benefits of investment could be fully exerted, and the ultimate goal of resources optimal allocation could be achieved. Because the pre-settlement audit was an extremely important process in the standardised project cost, there was a need to improve the audit level so that the effective management objectives could be achieved. Therefore, we introduced cloud computing to provide a certain basis for reducing audit cost effectively. The experimental results showed that the application of the cloud computing to the pre-settlement audit had produced positive effects, and the accuracy of the audit calculation could reach about 91%. Journal: Int. J. of Manufacturing Technology and Management Pages: 361-381 Issue: 4/5 Volume: 38 Year: 2024 Keywords: cloud computing; project cost management; pre-settlement work; review method. File-URL: http://www.inderscience.com/link.php?id=139522 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:361-381 Template-Type: ReDIF-Article 1.0 Author-Name: Jiandong Wang Author-X-Name-First: Jiandong Author-X-Name-Last: Wang Title: Investigation on security management risk assessment of accounting resource sharing under internet of things big data technology Abstract: While accounting resource sharing is convenient and saves a lot of time and energy, it also brings many potential risks to the enterprise. Therefore, how to protect and manage accounting resource sharing has become a top priority. This paper mainly studies the possible risks in the accounting resource sharing life cycle and the assessment of the security management risk of accounting resource sharing under the big data technology of the internet of things. This article will use various methods to evaluate the risk of accounting resource sharing security management, use information entropy and analytic hierarchy process to evaluate the uncertainty and risk size of accounting resource sharing security management risk, and use Markov chain and Bayesian formula to calculate the risk probability. The results show that the security protection efficiency of the optimised accounting resource sharing system has increased by 6.13%, and security management risks have been effectively controlled. Journal: Int. J. of Manufacturing Technology and Management Pages: 426-445 Issue: 4/5 Volume: 38 Year: 2024 Keywords: internet of things; big data; resource sharing; risk assessment; information entropy; analytic hierarchy process; AHP; Markov chain; Bayes rule. File-URL: http://www.inderscience.com/link.php?id=139524 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:426-445 Template-Type: ReDIF-Article 1.0 Author-Name: Umutcan Ayasandır Author-X-Name-First: Umutcan Author-X-Name-Last: Ayasandır Author-Name: Meral Azizoğlu Author-X-Name-First: Meral Author-X-Name-Last: Azizoğlu Title: Two-dimensional cutting stock problem with multiple stock sizes 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 maximise 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 two hours and the heuristics produce near-optimal solutions for the instances with up to 50 items in five minutes. Journal: Int. J. of Manufacturing Technology and Management Pages: 95-125 Issue: 2 Volume: 38 Year: 2024 Keywords: integer programming; heuristics; cutting stock problem. File-URL: http://www.inderscience.com/link.php?id=137486 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:2:p:95-125 Template-Type: ReDIF-Article 1.0 Author-Name: Nguyen Khac Minh Author-X-Name-First: Nguyen Khac Author-X-Name-Last: Minh Author-Name: Phung Mai Lan Author-X-Name-First: Phung Mai Author-X-Name-Last: Lan Title: Reallocation and imported technology: evidence from Vietnam manufacturing sector 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 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 show 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 126-142 Issue: 2 Volume: 38 Year: 2024 Keywords: manufacturing industry; reallocation process; static and dynamic decomposition; Vietnam. File-URL: http://www.inderscience.com/link.php?id=137487 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:2:p:126-142 Template-Type: ReDIF-Article 1.0 Author-Name: Olga Uflewska Author-X-Name-First: Olga Author-X-Name-Last: Uflewska Author-Name: T.C. Wong Author-X-Name-First: T.C. Author-X-Name-Last: Wong Author-Name: Michael Ward Author-X-Name-First: Michael Author-X-Name-Last: Ward Title: Capability management of manufacturing research centres: challenges and opportunities 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 UK's 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 143-171 Issue: 2 Volume: 38 Year: 2024 Keywords: capability management; manufacturing research centres; valley of death; technology capabilities; maturity; readiness; people; equipment; project; framework. File-URL: http://www.inderscience.com/link.php?id=137488 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:2:p:143-171 Template-Type: ReDIF-Article 1.0 Author-Name: J. Mahesh Author-X-Name-First: J. Author-X-Name-Last: Mahesh Author-Name: J. Jerlin Regin Author-X-Name-First: J. Jerlin Author-X-Name-Last: Regin Author-Name: T. Jarin Author-X-Name-First: T. Author-X-Name-Last: Jarin Author-Name: S.R. Boselin Prabhu Author-X-Name-First: S.R. Boselin Author-X-Name-Last: Prabhu Title: A comprehensive study of identification of microstructural analysis in various reinforced fly ash concretes 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 172-188 Issue: 2 Volume: 38 Year: 2024 Keywords: concrete; curing; fly ash; manufactured sand; X-ray diffraction spectrometry; XRD; scanning electron microscopy; SEM; microstructure. File-URL: http://www.inderscience.com/link.php?id=137489 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:2:p:172-188 Template-Type: ReDIF-Article 1.0 Author-Name: Hubert Wittke Author-X-Name-First: Hubert Author-X-Name-Last: Wittke Author-Name: Alan Ryan Author-X-Name-First: Alan Author-X-Name-Last: Ryan Author-Name: Ann Ledwith Author-X-Name-First: Ann Author-X-Name-Last: Ledwith Author-Name: Mark Southern Author-X-Name-First: Mark Author-X-Name-Last: Southern Title: Process innovation - the blind spot in product innovation. Development of a generic framework for the front-end in process innovation 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 (SLR) 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 189-212 Issue: 3 Volume: 38 Year: 2024 Keywords: process innovation; front-end; FFE; generic framework; product innovation; management; research gaps; systematic literature review; SLR; synthesis; manufacturing enterprises. File-URL: http://www.inderscience.com/link.php?id=138302 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:3:p:189-212 Template-Type: ReDIF-Article 1.0 Author-Name: Valérie Rocchi Author-X-Name-First: Valérie Author-X-Name-Last: Rocchi Author-Name: Daniel Brissaud Author-X-Name-First: Daniel Author-X-Name-Last: Brissaud Author-Name: Arko Steinwender Author-X-Name-First: Arko Author-X-Name-Last: Steinwender Author-Name: Arnaud Bocquillon Author-X-Name-First: Arnaud Author-X-Name-Last: Bocquillon Title: Technological and organisational factors to succeed in Industry 4.0 transition implementation: an empirical study Abstract: The fourth industrial revolution and its disruptive ICT technologies for production systems are crucial for the growth of European companies, especially SMEs. Nevertheless, few have reached the digital transformation with its expected performance yet. This paper aims to identify the critical success factors that support the 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 support organisations carried on in five Alpine Space countries. Eventually, five critical success factors were identified and ranked on a Likert scale. Twenty-six guidelines have been designed to support the industrys digital transition from these five critical success factors. The industry survey results contribute to accompanying industrial companies with improved diagnosis and monitoring tools. This empirical study allows for going beyond the current Industry 4.0 approaches and brings a new understanding of tools for factory of the future implementation. Journal: Int. J. of Manufacturing Technology and Management Pages: 213-235 Issue: 3 Volume: 38 Year: 2024 Keywords: Industry 4.0; manufacturing; SMEs; critical success factors; industrial organisation; empirical study. File-URL: http://www.inderscience.com/link.php?id=138303 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:3:p:213-235 Template-Type: ReDIF-Article 1.0 Author-Name: Christopher J. Kelly Author-X-Name-First: Christopher J. Author-X-Name-Last: Kelly Author-Name: Richard A. Wysk Author-X-Name-First: Richard A. Author-X-Name-Last: Wysk Author-Name: Ola A. Harrysson Author-X-Name-First: Ola A. Author-X-Name-Last: Harrysson Author-Name: Russell E. King Author-X-Name-First: Russell E. Author-X-Name-Last: King Author-Name: Brandon M. McConnell Author-X-Name-First: Brandon M. Author-X-Name-Last: McConnell Title: Automatic feature-based inspection and qualification for additively manufactured parts with critical tolerances 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 holes 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 utilised 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 236-264 Issue: 3 Volume: 38 Year: 2024 Keywords: additive manufacturing; CNC machining; hybrid manufacturing; inspection. File-URL: http://www.inderscience.com/link.php?id=138337 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:3:p:236-264 Template-Type: ReDIF-Article 1.0 Author-Name: Marcos Vido Author-X-Name-First: Marcos Author-X-Name-Last: Vido Author-Name: Salvatore Digiesi Author-X-Name-First: Salvatore Author-X-Name-Last: Digiesi Author-Name: Francesco Facchini Author-X-Name-First: Francesco Author-X-Name-Last: Facchini Author-Name: Wagner Cezar Lucato Author-X-Name-First: Wagner Cezar Author-X-Name-Last: Lucato Title: Collaborative robots in small and medium-sized enterprises: a field-based feasibility model Abstract: The Industry 4.0 (I4.0) revolution has led to new concepts and transformations toward technological innovations. In the manufacturing sector, the use of collaborative robots (cobots) 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 organisations regarding the adoption of cobots. Based on the literature, this paper aims to introduce a techno-economic feasibility model to evaluate the viability of using cobots in a shared workplace, with a focus on SMEs. Consistent with the papers 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 265-282 Issue: 3 Volume: 38 Year: 2024 Keywords: collaborative robot; SMEs; feasibility analysis; Industry 4.0; I4.0. File-URL: http://www.inderscience.com/link.php?id=138341 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:3:p:265-282 Template-Type: ReDIF-Article 1.0 Author-Name: Ganesh Dongre Author-X-Name-First: Ganesh Author-X-Name-Last: Dongre Author-Name: Aarya Kurlekar Author-X-Name-First: Aarya Author-X-Name-Last: Kurlekar Author-Name: Akshaan Kaware Author-X-Name-First: Akshaan Author-X-Name-Last: Kaware Author-Name: Piyush Kawade Author-X-Name-First: Piyush Author-X-Name-Last: Kawade Author-Name: Kshitija Kulkarni Author-X-Name-First: Kshitija Author-X-Name-Last: Kulkarni Author-Name: Harshada Kulkarni Author-X-Name-First: Harshada Author-X-Name-Last: Kulkarni Title: Comparative analysis of die-sinking EDM and near dry EDM for machining difficult-to-cut materials: Stainless Steel 316 and Hastelloy C276 Abstract: This paper explores the demand for precision machining of challenging materials and the limitations of traditional electro discharge machining (EDM). To overcome environmental impact and surface finish constraints, near dry EDM has emerged as a promising alternative. The study presents a comparative evaluation between die-sinking EDM and near dry EDM for machining Stainless Steel 316 and Hastelloy C276. Key performance parameters, including material removal rate (MRR), surface roughness (SR), and tool wear rate (TWR), are analysed to optimise the process. A novel dielectric mixture of glycerin and air is used in the experimental work. Results demonstrate that near dry EDM offers a superior surface finish and reduced tool wear; making it an environmentally friendly option. Near dry EDM achieved a 40% reduction in surface roughness for both alloys compared to die-sink EDM. Additionally, TWR showed a significant 40% decrease for SS316 and a notable 50% decrease for Hastelloy at high parameter settings in near dry EDM. Although a slight reduction in MRR is observed, the overall benefits position it as a promising technique for machining challenging materials. The findings provide valuable insights for selecting the most suitable EDM approach, enhancing modern manufacturing capabilities. Journal: Int. J. of Manufacturing Technology and Management Pages: 447-467 Issue: 6 Volume: 38 Year: 2024 Keywords: electro discharge machining; EDM; near dry EDM; NDEDM; material removal rate; MRR; tool wear rate; TWR; surface finish. File-URL: http://www.inderscience.com/link.php?id=143482 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:6:p:447-467 Template-Type: ReDIF-Article 1.0 Author-Name: Qing Zhang Author-X-Name-First: Qing Author-X-Name-Last: Zhang Author-Name: Na Tang Author-X-Name-First: Na Author-X-Name-Last: Tang Author-Name: Zhizhou Xu Author-X-Name-First: Zhizhou Author-X-Name-Last: Xu Title: Financial slack and the innovation behaviour of Chinese manufacturing firms: the moderating role of family ownership and digital transformation Abstract: This paper addresses whether financial slack influences the share of exploratory innovation in firms' innovation portfolio. Using the data of Chinese listed manufacturing firms over 2008-2021, we find that a higher level of financial slack leads to an increased share of exploratory innovation in firms' innovation portfolio. Further, we examine whether significant disparities exist between family firms and non-family firms in the effect of financial slack on the share of exploratory innovation, and find that the innovation portfolio of family firms shows less sensitiveness to the varying level of financial slack than non-family firms. Inconsistent with our prediction, digital transformation fails to unleash the potential of financial slack to trigger exploratory innovation. This paper contributes to depicting a more nuanced picture for the contingent impact of financial slack upon the composition of firms' innovation portfolio by uncovering the moderating roles of family ownership and digital transformation. Journal: Int. J. of Manufacturing Technology and Management Pages: 468-493 Issue: 6 Volume: 38 Year: 2024 Keywords: financial slack; exploratory innovation; innovation portfolio; family ownership; digital transformation. File-URL: http://www.inderscience.com/link.php?id=143483 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:6:p:468-493 Template-Type: ReDIF-Article 1.0 Author-Name: Weiping Jia Author-X-Name-First: Weiping Author-X-Name-Last: Jia Author-Name: Ling Wu Author-X-Name-First: Ling Author-X-Name-Last: Wu Author-Name: Xinya Zeng Author-X-Name-First: Xinya Author-X-Name-Last: Zeng Title: A study on the effect of RMB exchange rate fluctuation on technological innovation and total factor productivity Abstract: Based on the influence of RMB exchange rate fluctuation on the development of manufacturing firms, this research constructs a model from the perspective of reverse push to investigate the influence mechanism of exchange rate fluctuation on the total factors productivity (TFP) of manufacturing firms. The results show that: 1) the rise of the RMB exchange rate is conducive to the enhancement of the TFP of China's manufacturing firms, and the higher the ratio of intermediate goods import and export, the greater the effect of RMB appreciation on TFP of manufacturing firms; 2) the rise of the RMB exchange rate increases the number of patents applied by manufacturing firms and thus helps to make better the TFP; 3) compared with non-state-owned, high-tech and capital-intensive manufacturing firms, the rise of RMB exchange rate has a more noticeable influence on TFP improvement of state-owned, low-technology and labour-intensive firms; 4) reform of exchange rate formation mechanism in July 2005 enhanced the effect of RMB appreciation on TFP of manufacturing firms with more imports or fierce competition. From the perspective of the exchange rate, this research provides policy recommendations for Chinese manufacturing firms to increase TFP. Journal: Int. J. of Manufacturing Technology and Management Pages: 494-517 Issue: 6 Volume: 38 Year: 2024 Keywords: RMB exchange rate; research and development of reverse push; firm innovation; total factor productivity; TFP. File-URL: http://www.inderscience.com/link.php?id=143487 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:6:p:494-517 Template-Type: ReDIF-Article 1.0 Author-Name: Fateh Saci Author-X-Name-First: Fateh Author-X-Name-Last: Saci Title: The impact of industrial internet policy subsidies on corporate development: an empirical analysis of Chinese IIoT listed companies Abstract: Based on 139 industrial internet of things (IIoT) listed companies from 2014 to 2019, this paper conducts empirical research to further explore the impact of industrial subsidy policies mainly from two aspects: companies' R&D investment and revenue growth. The result shows that policy subsidies directly support companies' R&D investment, especially for industrial and private enterprises; whilst policy subsidies and companies' revenue growth are not significantly related. This indicates that policy subsidies have not been effectively transmitted to corporate performance. It is found that China's IIoT industry has achieved a rich level with various applications and multiple industrial platforms. Additionally, a well-structured policy framework has been realised. However, China's IIoT industry, whether in terms of volume or competitiveness, has a gap with the world's leading development level. This paper also proposes three suggestions for supporting IIoT policies in the conclusion. Journal: Int. J. of Manufacturing Technology and Management Pages: 515-539 Issue: 6 Volume: 38 Year: 2024 Keywords: industrial internet of things; IIoT; policy subsidies; R%D investment; revenue growth. File-URL: http://www.inderscience.com/link.php?id=143490 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:6:p:515-539 Template-Type: ReDIF-Article 1.0 Author-Name: Shuangling Wang Author-X-Name-First: Shuangling Author-X-Name-Last: Wang Author-Name: Huige Chen Author-X-Name-First: Huige Author-X-Name-Last: Chen Title: Path planning method of industrial intelligent welding robot based on cuckoo search algorithm 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, the non-collinear points are set in the running space of the welding robot, the running radius of the welding robot is calculated according to the determined centre of the circle, and the obstacle location is completed. Finally, the limited conditions of welding path planning of welding robot are set, and the cuckoo search algorithm is used to optimise 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 1-13 Issue: 1 Volume: 38 Year: 2024 Keywords: cuckoo search algorithm; industrial intelligent welding robot; route planning; D-H parameter method. File-URL: http://www.inderscience.com/link.php?id=137382 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:1-13 Template-Type: ReDIF-Article 1.0 Author-Name: Wang Cheng Author-X-Name-First: Wang Author-X-Name-Last: Cheng Title: Path coordination scheduling method of handling robot considering three-dimensional cargo space of intelligent warehouse Abstract: In order to optimise 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 are proposed. Firstly, a transport robot path coordination scheduling model considering three-dimensional storage is constructed, and then the improved grey wolf optimisation 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 500 m-2,500 m goods, the time can be shortened by 5-13 min, and the working efficiency of the handling robot can be improved. Journal: Int. J. of Manufacturing Technology and Management Pages: 14-26 Issue: 1 Volume: 38 Year: 2024 Keywords: intelligent warehouse; three-dimensional cargo space; carry; robot; path; coordinated scheduling. File-URL: http://www.inderscience.com/link.php?id=137383 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:14-26 Template-Type: ReDIF-Article 1.0 Author-Name: Yi Zhou Author-X-Name-First: Yi Author-X-Name-Last: Zhou Title: The dynamic multi project human resource allocation method of manufacturing industry based on multidimensional model 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. First, the total number of talents, workload and utilisation efficiency are determined. Then, a fuzzy set of human resources indicators is built, and the different hierarchical weights of each indicator calculate are calculated. Finally, 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 realise the intersection of index parameters in different regions, so as to realise 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 27-39 Issue: 1 Volume: 38 Year: 2024 Keywords: multidimensional model; PCA interval model; human resource allocation; fuzzy sets. File-URL: http://www.inderscience.com/link.php?id=137384 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:27-39 Template-Type: ReDIF-Article 1.0 Author-Name: Xiao-hua Qi Author-X-Name-First: Xiao-hua Author-X-Name-Last: Qi Author-Name: Guan-yi Wei Author-X-Name-First: Guan-yi Author-X-Name-Last: Wei Title: An optimisation control method of manufacturing whole process based on real-time information drive 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 51-65 Issue: 1 Volume: 38 Year: 2024 Keywords: information flow drive; real-time acquisition; production parameters; the whole process; firefly algorithm; optimal control. File-URL: http://www.inderscience.com/link.php?id=137385 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:51-65 Template-Type: ReDIF-Article 1.0 Author-Name: Jinrong Li Author-X-Name-First: Jinrong Author-X-Name-Last: Li Title: An intelligent buffer capacity allocation method for flexible production lines based on conjugate Bayes estimation 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 40-50 Issue: 1 Volume: 38 Year: 2024 Keywords: conjugate Bayesian estimation; flexible production line; prior information; buffer capacity; intelligent allocation of capacity. File-URL: http://www.inderscience.com/link.php?id=137386 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:40-50 Template-Type: ReDIF-Article 1.0 Author-Name: Linyan Pan Author-X-Name-First: Linyan Author-X-Name-Last: Pan Title: Dexterity control of multi-arm sorting robot based on machine learning 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 81-94 Issue: 1 Volume: 38 Year: 2024 Keywords: machine learning: multi-manipulator; robot; dexterity; translation transformation; rotation matrix; activation function. File-URL: http://www.inderscience.com/link.php?id=137387 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:81-94 Template-Type: ReDIF-Article 1.0 Author-Name: Geng Chen Author-X-Name-First: Geng Author-X-Name-Last: Chen Author-Name: Quzhi Huang Author-X-Name-First: Quzhi Author-X-Name-Last: Huang Title: An image detail enhancement of smart product UI interface based on stationary wavelet transform Abstract: To overcome the problems of low image segmentation accuracy, low image signal-to-noise ratio and long image enhancement time in traditional methods, an image detail enhancement method of smart product UI interface based on stationary wavelet transform is proposed. The Gaussian mixture model is used to obtain the image parameters of the UI interface of smart products, and the image of multiple pixels is divided into marked categories by the maximum posterior probability criterion, so as to realise the segmentation of image noise area and normal area. The two-dimensional stationary wavelet transform is performed on the noisy area, and the inverse stationary wavelet transform is performed on the stationary wavelet coefficients to obtain a reconstructed image with enhanced details. Experimental results show that the image segmentation accuracy of this method fluctuates in the range of 96%-98%, the signal-to-noise ratio is 55.3 dB, and the average image enhancement time is 66.9 ms. Journal: Int. J. of Manufacturing Technology and Management Pages: 66-80 Issue: 1 Volume: 38 Year: 2024 Keywords: stationary wavelet transform; smart products; UI interface; image detail enhancement; Gaussian mixture model; image reconstruction. File-URL: http://www.inderscience.com/link.php?id=137388 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:1:p:66-80 Template-Type: ReDIF-Article 1.0 Author-Name: Yiqiang Lai Author-X-Name-First: Yiqiang Author-X-Name-Last: Lai Author-Name: Yongjun Qi Author-X-Name-First: Yongjun Author-X-Name-Last: Qi Author-Name: Xianfeng Zeng Author-X-Name-First: Xianfeng Author-X-Name-Last: Zeng Title: Fuzzy system for image defect detection based on machine vision 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, 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 342-360 Issue: 4/5 Volume: 38 Year: 2024 Keywords: machine vision; image processing; image defect detection; fuzzy systems. File-URL: http://www.inderscience.com/link.php?id=139490 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:342-360 Template-Type: ReDIF-Article 1.0 Author-Name: Changxiu Dai Author-X-Name-First: Changxiu Author-X-Name-Last: Dai Title: Image dehazing network based on improved convolutional neural network 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 302-320 Issue: 4/5 Volume: 38 Year: 2024 Keywords: channel correction; convolutional neural network; CNN; image dehazing; pixel correlation; pre-emptive dehazing network; PDN. File-URL: http://www.inderscience.com/link.php?id=139491 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:302-320 Template-Type: ReDIF-Article 1.0 Author-Name: Yi Chen Author-X-Name-First: Yi Author-X-Name-Last: Chen Title: Economic investment risk prediction model and algorithm based on data mining method 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 283-301 Issue: 4/5 Volume: 38 Year: 2024 Keywords: investment risk; data mining; cluster analysis; factor analysis; decision tree. File-URL: http://www.inderscience.com/link.php?id=139492 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:283-301 Template-Type: ReDIF-Article 1.0 Author-Name: Guoqiang You Author-X-Name-First: Guoqiang Author-X-Name-Last: You Title: Design of computer image automatic processing system based on artificial intelligence algorithm 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 321-341 Issue: 4/5 Volume: 38 Year: 2024 Keywords: artificial intelligence; automatic processing; face recognition; feature extraction; automatic image processing method; AIPM. File-URL: http://www.inderscience.com/link.php?id=139501 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:321-341 Template-Type: ReDIF-Article 1.0 Author-Name: Pei Yang Author-X-Name-First: Pei Author-X-Name-Last: Yang Author-Name: Guoqiang You Author-X-Name-First: Guoqiang Author-X-Name-Last: You Title: Automatic human face recognition system of image processing based on BP neural network paradigm 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 382-405 Issue: 4/5 Volume: 38 Year: 2024 Keywords: DRL; face recognition; image semantics; texture classification; video analytics. File-URL: http://www.inderscience.com/link.php?id=139510 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:382-405 Template-Type: ReDIF-Article 1.0 Author-Name: Judan Hu Author-X-Name-First: Judan Author-X-Name-Last: Hu Author-Name: Shuang Tang Author-X-Name-First: Shuang Author-X-Name-Last: Tang Author-Name: Minjie Yang Author-X-Name-First: Minjie Author-X-Name-Last: Yang Title: Simulation of EPC consortium partnership stability and data based on prospect theory 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. Journal: Int. J. of Manufacturing Technology and Management Pages: 406-425 Issue: 4/5 Volume: 38 Year: 2024 Keywords: EPC consortium; cooperative stability; evolutionary games; prospect theory; system dynamics. File-URL: http://www.inderscience.com/link.php?id=139515 File-Format: text/html File-Restriction: Access to full text is restricted to subscribers. Handle: RePEc:ids:ijmtma:v:38:y:2024:i:4/5:p:406-425