International Journal of Simulation and Process Modelling (26 papers in press)
Service-oriented architecture-based design of bank-ATM and its verification with Petri net
by Amar Nath, Santanu Kumar Rath
Abstract: In the present era, IT-enabled business applications are very much observed to be pervasive and felt to be essential to manage an organisation. An organisation needs to update and upgrade its strategies to meet the challenges by adopting an IT-enabled solution to meet the agile customer requirements and market demand. An organisation has to embrace and underline technology that can be updated and modified without any severe bottlenecks. Service-Oriented Architecture (SOA) is one of the various architectural styles that provide agility to the organisation. SOA can help to meet different changes in requirements, viz., service composition, model-driven development, and service virtualisation. This paper illustrates the application of SOA in designing and implementing Automated Teller Machine (ATM) services, helpful in banking transactions. An ATM is a unit in the banking system, which is an embedded system that works on a distributed architecture. The incorporation of various services and their orchestration is implemented by using the Business Process Execution Language (BPEL) module under the OpenESB framework. However, in a complex and dynamic network environment, it is not easy to guarantee the quality of the BPEL process. So, it is very much essential to develop a proper BPEL process and validate it. In this study, the validation of the BPEL model is carried out by using the Petri net tool. The verification and validation activities are often considered essential to ensure the correctness of the system. The verification results obtained in this study are quite encouraging and prove validity.
Keywords: design of bank-ATM; improving bank-ATM performance; service-oriented architecture; orchestration of bank's services; verification with Petri net.
A novel energy conservation method for office building lighting system
by Xinyin Xu, Zhengtian Wu, Baochuan Fu
Abstract: There is a trade-off between human visual performance and energy cost. With an open office as the research object, personalised control with demand and daylight adaptation is considered in a lighting system with multiple illumination devices. Each luminaire and workspace is equipped with illumination sensors and intelligent units. The intelligent dimming model of the lighting system is established, and the optimal dimming value of the luminaire is determined by the constraint control algorithm. The summation of the power consumed by all LED lights and the other devices is used as the objective function. A simulation study was conducted in this research work with DIALux to verify the lighting system and control method. The simulation results show that the proposed control strategy can automatically adjust illumination in real time according to the change of daylight and personal demand.
Keywords: energy conservation; lighting system; constraint control; daylight; simulation.
Evaluating the impact of shared situational awareness on combat effectiveness in symmetric engagements
by Mahmoud Khasawneh, Nevan Shearer, Ghaith Rabadi, Shannon Bowling, Raed Jaradat
Abstract: The information age combat model (IACM) is a popular representation of Network Centric Operations (NCO). NCO is a military doctrine championed by the USA. This paper presents the results of a discrete event simulation (DES) of the IACM. The objective is to understand the impact of shared situational awareness on combat effectiveness in symmetric engagements. Symmetric in this context means that the battle engagements studied involved units having an equal number of sensors, deciders, and influencers. After model verification, the results of the linear and nonlinear regression analyses will be presented and discussed. The analyses have been carried out on the aggregated data first and then the data was disaggregated to focus on high percentage win engagements and evenly-matched engagements. The focus will be on highlighting the utility of the performance metrics defined and used in previous IACM research studies.
Keywords: network centric operations; information age combat model; shared situational awareness; discrete event simulation; performance metrics.
Using scenario-based simulation modelling to optimise aircraft inspection scheduling
by Rubayat Islam, Shengyong Wang, Chen Ling
Abstract: The main aim of this paper is to generate different visual simulation modelling scenarios for performing inspection operations on different Federal Aviation Administration (FAA) facilities. Different combinations of aircraft and routes are scheduled to design different scenarios for performing inspections. For assigning aircraft into the model, a study of FAA current fleet composition is made. To make the model robust, probabilistic distribution is introduced into the modelling approach. For every modelling approach or scenario, a various number of experiments with thousands of replications are scheduled to generate a maximum, minimum and average number of inspections over a year that can be performed through that modelling approach. Furthermore, a comparison of the different modelling approaches is made based on the number of inspections made by each model over a year.
Keywords: route planning; flight control; probabilistic approach; system design; transportation planning; robust model.
A conceptual process model to improve voter participation in Nigerian elections
by Ashiru Simon, Gabriel Lazarus Dams, Salome Danjuma
Abstract: Insecurity at every polling unit is one of the major reasons why the number of voters participating in Nigerian elections is continuously on the decrease. In the 2011 presidential election for instance, the number of people killed was estimated to be between 800 and 1000. More so, statistics has it that voter turnout for the presidential elections in 2007, 2011 and 2015 was 58%, 53.68% and 43.65%, respectively, showing a progressive decrease. In this paper, a process model for the election system currently used in Nigeria is designed to capture the voting system. The designed process model is modified by embedding an existing technology known as Unstructured Supplementary Service Data (USSD). A prototype is developed for demonstration. The adoption and deployment of the prototype will encourage the turnout of eligible voters and minimise the degree of rigging, human labour, loss of lives and improvement of overall voting time.
Keywords: Nigeria elections; USSD; conceptual process model; prototype; election process; voter participation.
Realistic scenario modelling for a building power supply and distribution system based on non-intrusive load monitoring
by Jundong Fu, Ying Zhao
Abstract: In power supply and distribution systems in buildings, the conventional designs of loads are fictitious, and it is difficult to find the vulnerabilities timely. In order to solve this problem, a realistic scenario modelling method is proposed. Aiming at the input of the power consumption data in a realistic scenario model, a non-intrusive load monitoring method is used, combined with sliding window switching event detection method of electrical appliance, and a sequence to short-sequence deep learning model is also established whose input vectors are composed of switching time and total power data. The input vectors in the deep learning model can be decomposed to the individual electrical appliances. Compared with CO and FHMM algorithm, the decomposition results of this model are excellent in precision, recall, F1 score and accuracy. Also, it is more practical and accurate to replace the estimated data with the electricity consumption data obtained by NILM in the realistic scenario modelling.
Keywords: realistic scenario modeling; non-intrusive load monitoring; deep learning; sliding window; sequence to short-sequence; attention mechanism.
Assessing escalator pedestrian traffic dynamics amid COVID-19 pandemic using hybrid simulation
by Konstantinos Mykoniatis, Anastasia Angelopoulou, Tianqi Gao Smith
Abstract: Pedestrian behaviour in urban spaces has abruptly changed amidst the COVID-19 pandemic owing to government-issued restrictions such as social distancing. It is unclear whether pedestrian behaviour will remain altered and/or urban spaces will be changed accordingly post-pandemic. Taking these changes and uncertainties, as well as the unique characteristics of pedestrian traffic as opposed to vehicle traffic, into consideration, this study creates a hybrid simulation model using the AnyLogic simulation software. The simulation model can be used to examine the efficiency of several types of escalator pedestrian behaviour in non-crowded scenarios, such as emergency/evacuation vs. regular operation, capacity and number of available escalators, escalator dimensions (e.g., height and length) and speed, and pedestrian preference (e.g., standing vs. walking). This generic simulation model allows future users to evaluate the efficiency of the escalator operation scenarios they would like to simulate by providing output measures such as time spent in system and throughput and allowing customisations of escalator dimensions and pedestrian-related parameters based on user-specific requirements.
Keywords: hybrid simulation; escalator; pedestrian; COVID-19 pandemic; social distancing.
Acoustic performance and modal analysis for the muffler of a four-stroke three-cylinder inline spark ignition engine
by Sushovan Chatterjee
Abstract: This work presents a concise analytical report on four suggested design modifications (geometrical configuration of the resonating chamber) of a practical muffler model based on acoustic performance and reduction of back pressure. The existing model shows a very low acoustic transmission loss (15.8 dB) with a back pressure of nearly 2.52
Keywords: muffler; acoustic transmission loss; back pressure; modelling; simulation.
Traffic jams prediction using hazardous materials transportation accident simulation
by Luiz Reis, Sergio Luiz Pereira, Eduardo Mario Dias, Maria Lidia Rebello Pinho Dias Scoton
Abstract: This paper presents a simulation study of potential benefits in traffic jams due to improvements in hazardous materials management. The leak of hazardous materials put in danger human lives and the environment. Hazardous materials transportation is indeed necessary to cities, and complex traffic control is necessary to avoid and reduce accidents, but it is very expensive, therefore the cities have insufficient traffic surveillance. The combined use of smartphone sensors and an integrated control system for tracking, management, monitoring, and controlling hazardous materials transportation is a non-intrusive and cost-effective solution. Simulation as a reliable prediction is an effective support to traffic management.
Keywords: computer simulation; traffic engineering; computer networks; communication systems.
Modelling and assessing public health policies to counteract Italian measles outbreaks
by Giovanni Scire'
Abstract: This study aims to understand, through explanatory research, the key factors that led to the 2017 measles outbreak in Italy, the causes of the low level of immunisation and the causes of possible cyclical phenomena of measles epidemics. This topic's comprehension has required a holistic approach, merging epidemiological aspects, socioeconomic aspects (including the evolution of mistrust in vaccinations, infodemy and fake news) and health law constraints. A specific SIR System Dynamics (SD) model was built to reproduce the relevant cause-and-effect relationships between social interactions, the public institutions behaviour and the measles outbreaks. SD results permit the assessment of the health policies to counteract the measles outbreaks. Findings, limits and further research recommendations are briefly reported in the conclusions.
Keywords: system dynamics; infodemic; measles; communicable diseases; SIR model; vaccination; public health.
Lightweight design of semitrailer based on topology optimisation and response surface methodology
by Shuwen Zhou, Jichao Xu
Abstract: To improve the fuel economy and transportation efficiency of semitrailers, this paper conducts a lightweight study on a semitrailer frame. This paper mainly uses the finite element method and combines topology optimisation and response surface method to optimise the suspension and frame. After the optimisation analysis, the best installation size of the suspension is finally obtained, and the weight of the frame is reduced by 507.8 kg to meet the material strength, which achieves a good lightweight effect. The lightweight method of the semitrailer proposed in this paper can provide a feasible solution for the lightweight of road transport vehicles.
Keywords: semitrailer; finite element analysis; lightweight; topology optimisation; response surface methodology.
DARSV: a dynamic agent routing simulator for VANETs
by Samira Harrabi, Ines Ben Jaafar, Khaled Ghedira
Abstract: In this paper, a novel Dynamic Agent Routing Simulator for Vehicular ad-hoc networks (DARSV) is presented. The main purpose of the DARSV simulator is to realise a successful large-scale simulation of the agent-based routing approach in vehicular networks. To reach this goal, the proposed simulator combines the Java Agent DEvelopment (JADE) which is a powerful Multi-Agent System (MAS) framework, with the Dynamic Ad Hoc Routing Simulator (DARS) that takes into account the dynamic nature of environment networks. The simulation results are discussed to evaluate the efficiency and the performance of the proposed simulator.
Keywords: large-scale simulation; network simulation; agent based routing protocol; vehicular ad-hoc networks; multi-agent systems.
Simulation of unmanned ship real-time trajectory planning model based on Q-learning
by Jindong Liu, Jie Yang, Zhiqiang Guo, Hui Cao, Yongmei Ren
Abstract: In view of the challenge in autonomous navigation of unmanned ships where environmental conditions are complicated, this paper proposes a global trajectory planning model with local risk collision avoidance. The model establishes MAKLINK global connectivity map from an original sea area, and provides global trajectory planning strategy based on ACO algorithm, and then introduces Q-learning algorithm to realise local risk collision avoidance, thus achieving real-time trajectory planning for unmanned ships. Compared with traditional models, our proposed one reduces level of complexity in environmental modelling, without bringing path uncertainty due to the presence of reinforcement learning, and also has faster trajectory convergence and shorter path length. This work would bring meaningful insights to future autonomous navigation research.
Keywords: unmanned ship; real-time trajectory planning; ACO algorithm; Q-learning.
A consolidative evaluation of extracted EGG speech signal for pathology identification
by Satyajit Pangaonkar, Reena Gunjan
Abstract: Speech as a natural and effective way of communication needs an appropriate analysis. This assessment is mainly used to quantify specific signals with various irregularities. The Electroglottograph (EGG) helps to understand the functional utility of the exact state of the vocal fold in terms of vibration stage. But noise, gender dependencies and spectral measures limitations lead to inadequate description of vibratory state of the vocal fold. The proposed integrative approach of parametric evaluation using software tools such as FonaDyn (phonatory dynamics), which analyse the vibrational modes using clustering. Also, a Multidimensional Voice Program (MDVP), which estimates normative based parametric statistics along with PRAAT (software for speech analysis in phonetics) and BioVoice (perceptual interpretation of speech signal), defines spectrographic relational stratagem. Interfacing FonaDyn, MDVP, and PRAAT and BioVoice with EGG experimentally identifies variability in the different parameters and enhances the graphical performance of the canonical grade statistical analysis for a phonatory gap pathology. The parametric accuracy of the diagnosis in terms of parameters will be effective for post-processing of the speech analysis.
Keywords: electroglottograph; multidimensional voice program; PRAAT; BioVoice; clustering; phonatory gap.
Modelling and simulation of ultrasonic descaling in a heat exchanger
by Guorong Liu
Abstract: Heat exchangers are widely used in the petrochemical industry, but long cycle operation leads to the generation of scaling and the reduction of heat transfer coefficient. However, the traditional scale removal method is not convenient to operate with high cost. In this paper, a kind of ultrasonic descaling technology is designed, and the propagation model of an ultrasonic wave in the heat exchanger is established by using B-P neural network, including the propagation model of the ultrasonic load on the tube plate and the propagation model of the ultrasonic load in the medium. Based on the influence of two different ultrasonic loading modes, the propagation mechanism of the ultrasonic load on the tube plate was obtained by simulation research. Finally, the propagation mechanism model of the ultrasonic wave in the heat exchanger is established successfully through experimental verification.
Keywords: ultrasonic scale removal; heat exchanger; B-P neural network; simulation.
Thermal conductivity of bimetal Al-Cu: molecular dynamics simulation
by Junaidi Syarif, Khaled Badawy, Mohamed Hisham, Hussien Hussien
Abstract: In this study, the phonon thermal conductivity of bimetal Al-Cu was modelled using molecular dynamics. The conductivities of pure Cu and Al were calculated and discussed first to verify the adopted methodology. The behaviour of the heat current autocorrelation function was discussed for the two pure metals and the bimetal. The values of thermal conductivity at different temperatures for the pure metals were reported and the results were correlated to similar computational works. The thermal conductivity was found to drop as the temperature increased. The bimetal Al-Cu thermal conductivity and the variation with temperature were reported. It was found that the bimetal Al-Cu has a very low conductivity compared with the pure metals. It was found that the drop in thermal conductivity was due to an increase in lattice defects and distortions arising from the bimetal interface. The drop in thermal conductivity as the temperature increases still holds and follows a linear relation.
Keywords: Green Kubo relation; phonon; lattice distortion; interface.
Stochastic modelling and availability analysis of a repairable system of a milk processing plant
by Narendra Kumar, P.C. Tewari, Anish Sachdeva
Abstract: This paper describes the performance evaluation of the pasteurising system of a milk processing plant in terms of its operational availability. For the stochastic modelling and analysis, Markov chains has been applied. Particle Swarm Optimization (PSO) technique is implemented for optimising the results obtained. The optimum combinations of failure and repair rates for various subsystems can be useful in decision making, such as maintenance priorities, spare parts and repairs, etc. Based on this a Decision Support System (DSS) has been developed which indicates the most critical components of the system that need the utmost care while setting maintenance priorities.
Keywords: availability; DSS; Markov chains; PSO; RAM.
Modelling deployment pipelines for co-simulations with graph-based metadata
by Stefan Reiterer, Michael Kalab
Abstract: In complex mechatronic systems, co-simulations need to be conducted to test the behaviour of larger systems. DevOps tools and methods are used to make the development of simulation models for mechatronic systems efficient. For this purpose, a graph-based metadata model is introduced to describe the process to autogenerate code for build servers. It also makes build pipelines reusable and suitable for safety critical software components. We discuss how DevOps processes for mechatronic systems are modelled as a graph, define the data structure formally and present algorithms for automatic code generation and representation within a NoSQL graph database. In addition, we compare different optimisation strategies for build and deployment schedules.
Keywords: metadata; data sharing; computer-supported collaborative work; code generation; NoSQL graph database; mathematical process modelling; combinatorial optimisation.
Special Issue on: I3M 2019 Simulation and Process Modelling of Tomorrow How 4.0 is Affecting R&D in Multiple Domains
Simulation-based optimisation for worker cross-training
by Johannes Karder, Andreas Beham, Viktoria A. Hauder, Klaus Altendorfer, Michael Affenzeller
Abstract: Worker cross-training is a problem arising in many companies that involve human work. To perform certain activities, workers are required to possess certain skills. Cross-trained workers possess multiple skills, which enables a more flexible deployment, but also incurs higher costs. Thus, companies seek to balance the available skills such that customer deadlines can be met in a cost-efficient way. In this work, we compare solution approaches for a simulation-based problem formulation with three objectives. We apply evolutionary multi-objective optimisation to a production system scenario with two lines and six workstations. Their performance is compared for a hard scenario where cross-training is essential to achieve high service levels. Results indicate that the algorithms are able to solve this three-objective formulation quite well using the described encoding and operators. Employing this technology at companies could lead to better qualification strategies and a better contribution of qualification efforts to company goals.
Keywords: worker cross-training; workforce qualification; encoding; multi-objective optimisation; NSGA-II; MOEA/D.
Special Issue on: ISM 2019 New Challenges and Solutions for Industry 4.0 and Smart Manufacturing
Blockchain-based solutions for agri-food supply chains: a survey
by Giovanni Mirabelli, Vittorio Solina
Abstract: In recent years, interest in blockchain technology has grown considerably, owing to its multiple properties, such as transparency, immutability, traceability, and security. Considering the significant number of recently published contributions about the use of blockchain-based solutions in the agri-food sector, in this paper we aim to collect and catalogue them. The main purpose is the identification of research trends and possible barriers to the large-scale spreading of this disruptive technology. Through a well-structured four-step research methodology, we systematically review 48 papers. The main result is that blockchain can be used not only to ensure complete food traceability, but also to protect workers' rights, limit the power of supply chain intermediaries, protect market prices, and enable reward mechanisms for the development of sustainable initiatives. However, there are still some open issues that limit its large-scale diffusion: lack of shared standards, limited number of real case studies, resistance by stakeholders, and restricted scalability.
Keywords: blockchain; agri-food supply chain; food traceability; internet of things; smart contract.
Construction logistics: a simulation case study to improve performance process
by Kamal Jaafar
Abstract: Logistics in construction in general is an old topic, which has been researched and studies by many scientists, engineers, and researchers. However, little attention was given to logistics management in the precast industry and was relatively ignored, especially in the United Arab Emirates (UAE), compared with the conventional construction industry (cast in-situ). This paper will talk in details about the forgotten part in construction logistics, which is the precast construction logistics management: specifically, the management of the precast stockyard layout in the precast concrete products industry. Designing an effective precast stockyard with effective storage and structural precast element retrieval is a very complex process. The complexity is because of the massive heavy precast elements products, unique lifting and tilting requirements, and the large number of panels produced and stocked. Thus, the paper will discuss how to ensure efficient storage and dispatch of precast elements, ease of rotation of precast elements within the precast stockyard, and a smooth precast element retrieval process from any stockyard. In addition, the paper will show how an effective stockyard layout can reduce the dispatch time, loading time, and queuing time of the precast elements within the stockyard. Finally, the paper will include simulation modelling using ARENA software to optimise, design, and test the new stockyard layout that we established and compare it with the current status of the precast stockyard. A 'what if' analysis will be implemented from the simulation model in order to cover various stockyard conditions, such as increased product production in the future.
Keywords: logistics; process optimisation; ARENA; stockyard management; construction.
Special Issue on: I3M2020/ISM2020 Simulation and Process Modelling in Industry and Logistics New Advances in Theory, Methods and Applications
Systems of distributed artificial intelligence for analysis of oil product transportation processes: evidence from Russia
by Elena Serova, Daniil Shklyaev
Abstract: At present, the use of Artificial Intelligence (AI) methods and tools is an essential component of management information systems for a company to succeed in a rapidly changing environment. Agent-based modelling systems as systems of distributed AI must be considered nowadays as an obligatory stage of decision-making in Russian oil and gas companies, which use modern information technologies actively. The paper is focused on the description and comparative analysis of system dynamics and agent-based modelling, used for intelligent decision support systems development in transport logistics. The main goal of this research is evaluation of the multi-agent system's role for decision-making processes and management information systems development and creating the model of logistics processes (the processes of oil and oil products transportation, loading, and unloading). The work is based on a generalisation of theoretical researches in this area along with international practices and domestic experience.
Keywords: artificial intelligence; distributed artificial intelligence systems; simulation; agent-based modelling; transport logistics; processes of oil and oil products transportation.
Simulation-based cost optimisation of a risk mitigation strategy in an assembly job manufacturing process: a case study from the offshore wind industry
by Adolfo Lamas-Rodríguez, Javier Pernas-Álvarez, Inés Taracido-López, Santiago-José Tutor-Roca
Abstract: Despite holding very high expectations regarding installed capacity and planned investments, offshore wind energy is currently facing important challenges to align itself with the levelised cost of other renewable energies, such as solar power and onshore wind. In this context, we aim at putting DES optimisation at offshore winds disposal and leveraging its advantages proved in other areas. To accomplish this, we have performed a DES-based optimisation of the routing strategy and the net income of an offshore wind foundations manufacturing project affected by very important delays due to Covid-19 impact and material supply issues. The problem applies to a constraint-based multi-level assembly job shop where we use dispatching rules to model the routing decision. Overall, we have provided the company with an optimised schedule, due dates, expected penalties, expected net income and a detailed ongoing DES model to be used in further stages of the project.
Keywords: discrete-event simulation; simulation-based optimisation; offshore wind; Industry 4.0; dispatching rules; assembly job-shop; constraint-based simulation.
A fuzzy cognitive map based approach to prioritise environmental objectives in the environmental management systems of ports
by Maria Drakaki, Panagiotis Tzionas
Abstract: Increased attention is being paid to the environmental and social impacts of ports, adding pressure to the port authorities towards sustainable port management and development. Environmental priorities of European ports have changed over the years, however environmental aspects such as energy consumption, carbon footprint and waste are being monitored increasingly. A certified environmental management system (EMS) and definition of objectives and targets for monitoring environmental aspects are being used to assess the environmental management performance of ports. This paper proposes a modelling methodology based on Fuzzy Cognitive Maps (FCM) to prioritise environmental objectives and targets as part of an EMS for a port, and shows a case study for the port of Thessaloniki. The case study builds on the results of a previous study that employed the Ecological Footprint (EF) methodology to assess the CO2 emissions-related EF of the port of Thessaloniki for the time period 2008-2009.
Keywords: ports; fuzzy cognitive map; modelling; simulation scenarios; ecological footprint; environmental management systems; environmental objectives.
Discrete event simulation for the investment analysis of offshore wind manufacturing processes
by Adolfo Lamas-Rodríguez, Inés Taracido-López, Javier Pernas-Álvarez, Santiago-José Tutor-Roca
Abstract: Spreadsheets are by far the most widely employed tool to perform investment analysis. However, in operations research, their rigidness ignores the variability inherent in stochastic systems and neglects important factors that may affect the feasibility of the investment. Hence, we present here an innovative use of discrete event simulation for investment analysis by means of two case studies taken from the offshore wind industry. To do so, we implemented an algorithm on top of a 3D DES model, which performs the investment analysis in parallel with it. Results are shown by means of net present value and internal rate of return. In this way, we consider at once process variability and variable economic factors, such as discount rate, thus achieving more reliable results. Finally, we set investment parameters as target variables in the optimiser to obtain the best scenario regarding both productivity and profitability.
Keywords: investment analysis; discrete event simulation; optimisation; offshore wind; Industry 4.0; net present value; internal rate of return.
Special Issue on: ISSPM2020 Advances in Simulation and Process Modelling
A methodology to characterise simulation models for discovery and composition: a system theory based approach to model curation for integration and reuse
by Bernard Zeigler
Abstract: We make a strong assumption that we can extract the necessary and sufficient information needed to decide whether a simulation model is suitable for an analyst's problem and that it contains information on how to be configured, integrated, and executed. This assumption allows us review an approach that is founded on the theory of modelling and simulation and employs tools to develop, simulate, and apply models expressed in the Discrete Event System Specification (DEVS) formalism, a sound systems theory-based computational methodology for system-of-systems model development and deployment. This foundation allows us to discuss how to apply the well-developed theory to curate simulation models so that they can more easily be discovered from a model repository given analytical objectives. After outlining the methodology, we place it in a broader context in which web- and cloud-based technologies are employed for integration and to enable modelling and simulation as a service. Significant technical challenges are described that require continued research and development.
Keywords: DEVS; theory of modelling and simulation; model curation; reusability; composability.