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This paper proposes a digital twin enhanced approach for optimizing collaborative production scheduling in multi-enterprise manufacturing systems. A multi-objective model is developed incorporating practical constraints such as limited time windows, different production capacities, and transportation considerations. To solve the model, an Improved Non-dominated Sorting Genetic Algorithm (INSGA-II) is designed with specialized operators and strategies. The digital twin simulation is enriched with Multi-objective Decision Making based on Interaction Structures (MDIS) to obtain higher-quality solutions. Experiments demonstrate that the MDIS digital twin approach reduces manufacturing lead times and costs while improving utilization and quality compared to standard methods. This research provides an effective optimization framework to leverage cloud manufacturing resources across organizations. [ABSTRACT FROM AUTHOR]

The objective of the study is to analyse the scientific production on optimisation via simulation (OvS) applied to reverse logistics. Therefore, a systematic literature review on this area was carried out based on articles published in the main scientific databases during the last 30 years. We analysed about 70 articles published in several journals, and the state of the art regarding the adoption of OvS in reverse logistics problems was explored. This article fills some important questions about the adoption of this approach and might be useful for researchers and professionals in their developments related to this research field. Finally, we highlight some issues and research opportunities. [ABSTRACT FROM AUTHOR]

Researchers believe that Industry 4.0 is the new industrial revolution. In this case, we highlight the critical role of decision support tools, such as Simulation and Digital Twins (DT) models, that might help decision-making in strategic decisions in the industry. Additionally, Green Supply Chain is a theme that has been widespread due to all the issues involving pollution and tax breaks that some government offers to industries. Furthermore, enterprises worldwide are becoming more aware of environmental issues. In this subject, an area that has been emerging but is not significantly addressed in the literature is Reverse Logistics (RL). Thus, this work aims to analyse how Simulation and DT are helping RL in the Industry 4.0 context, answering some questions that may support future researchers to begin their studies in the area. [ABSTRACT FROM AUTHOR]

This paper introduces a fault diagnosis and prediction framework for petroleum machinery production systems, addressing the need for more efficient and reliable fault handling in the face of complex signals. Utilizing the Complete Ensemble Empirical Mode Decomposition (CEEMD) and permutation entropy, it extracts signal features to analyse system dynamics. An Adaptive Variational Mode Decomposition (VMD) and optimized Extreme Learning Machine (ELM) simulation model enhances diagnostic accuracy through signal processing and fast learning capabilities. This approach not only elevates fault diagnosis precision but also supports the maintenance and health management of petroleum machinery systems, offering significant theoretical and practical benefits. [ABSTRACT FROM AUTHOR]

This paper presents a simulation approach to enhance the performance of heuristics for multiproject scheduling. Unlike other heuristics available in the literature that use only one priority criterion for resource allocation, this paper proposes a structured way to sequentially apply more than one priority criterion for this purpose. By means of simulation, different feasible schedules are obtained to; therefore, increase the probability of finding the schedule with the shortest duration. The performance of this simulation approach was validated with the MPSPLib library, one of the most prominent libraries for resource-constrained multiproject scheduling. These results highlight the proposed method as a useful option for addressing limited time and resources in portfolio management. [ABSTRACT FROM AUTHOR]

Research on collaborative manufacturing process modelling and simulation is of great significance in improving production efficiency and product quality, reducing costs, promoting collaborative work, and supporting decision-making. However, current studies have not offered the optimal costs of node enterprises participating in collaborative manufacturing, and ignored the impact of demand uncertainty of suppliers, manufacturers and customers on costs and economic benefits. Therefore, this paper aimed to study the collaborative manufacturing process modelling and simulation of production cost and economic benefit accounting analysis. First, this paper summarized three cost types, conducted cost accounting for the collaborative manufacturing process, and analysed its economic benefits. Second, based on the basic timed automata (TA) model, this paper used a timed input/output automata with port labels (Lp-TIOA) for modelling test cases of the simulation system. Finally, the experimental results verified the effectiveness of the constructed simulation model. [ABSTRACT FROM AUTHOR]

While large enterprises are actively preparing for digital transformation by leveraging technologies such as digital twins, smaller companies face challenges due to economic constraints and market uncertainties, leading to a relative lack of awareness and readiness. To address this situation, this study proposes a digital twin development framework tailored for small and medium-sized enterprises (SMEs). This framework utilizes attachable IoT devices for real-time collection of manufacturing data and leverages public server systems for data management. Moreover, it enables the refinement and optimization of digital twins by training machine learning models on collected data. Additionally, the framework includes the integration of simulation models and machine learning models for comprehensive digital twin modelling. Finally, the paper suggests a process for applying and validating this framework in real manufacturing companies, demonstrating the effects of digital twin implementation on productivity enhancement in the production lines of two SMEs. [ABSTRACT FROM AUTHOR]

The reliability of high-voltage circuit breakers (HVCBs) depends critically on the dynamic characteristics of their hydraulic operating mechanisms (OMs). However, previous analyses have been limited to discrete components due to the lack of models capturing multi-physics couplings. This paper proposes a novel co-simulation approach for hydraulic OMs that enables system-level analysis. Specifically, the hydraulic system is modelled using the lumped parameter method, and the transmission mechanism is modelled via finite element analysis. The subsystem models exchange inputs and outputs through shared memory, realizing coupling without compromising simulation performance. Experiments on a 550 kV HVCB validate that the model accurately captures OM transient responses. The co-simulation framework has diverse capabilities, including predicting dynamics under varied operating parameters and quantifying stress distributions and response evolution patterns. Overall, this paper proposes an advanced multi-physics analysis capability for hydraulic OMs to support reliabilityoriented design and optimization. [ABSTRACT FROM AUTHOR]

Marine gas-water separator is mainly used to filter impurities in the air for gas turbine, and it also needs to have certain anti-impact ability in engineering application. In order to study its impact resistance, this paper used the method of combination of simulation and experiment. Firstly, the material properties of 5083 aluminium alloy were determined. On the basis of this, the drop test under different acceleration was carried out. Then ABAQUS software was used to carry on the drop simulation analysis and antiknock simulation analysis. The feasibility of the simulation method was verified by comparison of simulation results and experimental results. The following conclusions are obtained: the impact of 5 g-33 g drop will not affect the operation of the gas-water separator; the impact of guide vane's transverse fall on the gas-water separator is less than that of guide vane's longitudinal fall; the direction with guide vane's support has stronger anti-detonating performance than that without guide vane's support. The conclusions drawn in this paper can be used for specific optimization and protection in practical use, and provide a certain reference for the impact performance field of Marine gas-water separator. [ABSTRACT FROM AUTHOR]

The printing company's process performance depends on the possibility of providing requested products and managing the existing constraints of fixed machine layouts and high setup times between different products. Process inefficiencies caused by these factors reflect on throughput, production times, and resource utilization. The changes that improve one part of the production system usually affect other parts, needing additional optimization, and it is very useful to test the feasibility of proposed solutions with simulation before implementation. This paper presents a new algorithm for continuous improvement of enterprises performance, combining the lean approach with cellular manufacturing, and simulation. The performance is observed in a way that a certain setup influences the system in its entirety, rather than on a specific part of that system. The results are presented through models developed within the production optimization phase, representing various ways in which the continuous improvement algorithm can unfold. Each of them comes with its advantages and disadvantages, all intending to create more efficient production processes that generate less production waste. [ABSTRACT FROM AUTHOR]

The research of multiple inspection robots' path simulation planning helps to improve the inspection ability and efficiency of the multi-robot system. This paper studies the problem of cooperative optimization and simulation of multiple robots for multiple inspections in intelligent manufacturing. A dynamic simulation model of the inspection robot is used to construct the state equation of the multirobot inspection simulation system. The square grid is used to decompose the intelligent manufacturing workshop area and simulate the workshop space. With reinforcement learning, a multi-robot patrol simulation system is created for full coverage path simulation planning. The results show the effectiveness of the system for cooperative optimization control and reasonable path planning. [ABSTRACT FROM AUTHOR]

In the paper, we solved the problems regarding the improvement of the production process of allocating material to the inlet of a production hall using the Plant Simulation software in a selected company. The solved problematics are high costs for the shipping company, elimination of the necessity to transfer the semi-finished product from the external warehouse to the production hall and non-effective layout. We deal with the characteristics of the current state of the production process in the production company and create its model in Plant Simulation. Thereafter we propose solutions that can make that process more efficient. The software enables the comparison of complex production alternatives. [ABSTRACT FROM AUTHOR]

Digital Twin (DT) is considered the most modern simulation method when it comes to tightly connect the real and virtual worlds to produce accurate simulation models of constant use to aid stakeholders in decision making. This method has been used more intensively in the manufacturing sector, but its use has spread to other sectors of great relevance in the economy, such as the retail industry. The contribution of this article to existing research is to present a Systematic Literature Review (SLR) addressing the state-of-the-art of the potential use of Digital Twins (DTs) to support decision making in the retail field. The main findings illustrate a considerable appearance of case studies applied directly in the sector, a strong investment in research focused on supply chains, an extensive use of simulation models and sensors, however, that mostly make use of secondary data and are not completely autonomous. Summary tables of the main benefits, opportunities and challenges in applying DTs in the retail sector are also presented. [ABSTRACT FROM AUTHOR]

The existing mathematical analysis approaches for the management of product manufacturing process cannot satisfy the global optimization and high feasibility required for product manufacturing. Neither do they reflect the actual production situation accurately and comprehensively. Therefore, this paper explores the simulation and modelling of management decisions in multi-variety small-batch product manufacturing process in discrete production environment. Firstly, the management knowledge in product manufacturing process was expressed mathematically, and the product manufacturing system was modelled in discrete production environment. Then, the flow of the interactive simulation model was explained, along with the realization steps of the model. Taking a real multi-variety small-batch production unit as the engineering background, an empirical analysis was carried out to detail the interactive simulation of the line change management for the production lines in the management system of the product manufacturing process, and to build a simulation model for the product manufacturing system. The simulation model was proved effective through simulations. (Received in April 2022, accepted in July 2022. This paper was with the authors 1 month for 2 revisions.) [ABSTRACT FROM AUTHOR]

Intelligent manufacturing automation is a future trend, and optimizing production resource control using blockchain technology is a meaningful research topic. Existing studies have limitations, such as varying PSCO-PC models and insufficient flexibility in simulation models. This paper proposes a novel blockchain-based PSCO-PC strategy for intelligent manufacturing. It details the PSCO-PC model, improving the matching rationality and applicability of simulation system functions. The adaptive difficulty concept is introduced to address data throughput and consensus mechanism issues. Calculation steps for solving the optimal package revenue of PSCO matching records are provided. Experimental results confirm the effectiveness of the proposed simulation model and PSCO-PC strategy. [ABSTRACT FROM AUTHOR]

In this paper, we first propose online and offline channel incentive models (CIM) with consideration of the consumers’ rational choices to solve and simulate the channel incentive problem (CIP) for supplier. We investigate whether the increase in demand along with channel incentive activities is enough to compensate for the decrease in the supplier's marginal revenue and retailers could benefit from the increase in market demand when retail channel information reference factor satisfies a certain threshold value. Our results show that decision preference of channel members is influenced by the reference factor and marginal revenue. Furthermore, the numerical achievements indicate that there is a unique optimal channel incentive coefficient related to the rational choices in benchmark channel incentive model (BCIM) for omnichannel. Both suppliers and retailers would benefit from the increased orders. Channel efficiency is improved from 72 % to 79 %. And the supplier profit function is a concave function of supplier's input in the offline channel incentive in the offline CIM. [ABSTRACT FROM AUTHOR]

Manual assembly operations are often the bottlenecks of production processes. Usually, in order to find out, what the throughput of these manual assembly operations will be, it is first necessary analysing them in the context of the workstation and the whole processes as well. For these analyses, one of the most useful tools is the use of simulation. Despite existing several complete software for these purposes, they often demand significant time and effort to create good simulations. Sometimes, however, it is just enough to simulate a few key aspects of the assembly process to get key results, which are often the base for immediate and/or further process improvement. In these cases, creating a special analytical tool that allows efficiently obtaining a sufficiently good solution to the given problem becomes a viable and convenient option. This paper presents an assembly simulation and analysis tool designed and created in Microsoft Excel by the authors. The tool is useful for quick analyses of assembly tasks without the need of having to engage in creating complex 3D models and extra analyses. The proposal is implemented into a practical case study, which allows verifying its validity. [ABSTRACT FROM AUTHOR]

To improve the recovery for corner coal left over in mines, taking the Xin'an Mine in China as the research object, the gradual increase support mining method for recovering corner coal is proposed in this study and the evolution of the overlying strata pressure is investigated. The dynamic process of the overburden roof in the corner coal and the hydraulic support were simulated by using FLAC3D software. Results show that, under the gradual increase support mining, the abutment pressure over the mining working face is less than 21 MPa. The overlying rock over the coal seam roof forms a periodic breaking--collapse cycle with a periodic pressure step distance of 10 m and the hydraulic support load is 13-25 MPa. Based on that, the gradual increase support mining method including a scheme of three supports and three chutes adding for every 9 m is designed and the corner coal is fully recovered. The obtained conclusions provide a significant reference for predicting strata movement over the corner coal, which can help aid in designing such mining method in engineering applications. [ABSTRACT FROM AUTHOR]

The article discusses the problem of total waste separation in the frame of a computer simulation design of these systems. The aim of the article is to employ computer simulation, modelling and logistics for the needs of total separation of waste and its recycling into the form of raw materials and re-usable resources in practice. The results of the computer simulation show that by using total separation and waste recycling in the specifically analysed region, it is possible to produce approximately 7700 tons of recycled paper, 2400 tons of multilevel packages, 8000 tons of glass, 3000 tons of old textiles, 3500 tons of iron, approximately 1500 tons of non-ferrous metals, approximately 2700 tons of wooden pallets, approximately 1200 tons of rubber granulate, to process approximately 800 tons of dangerous waste, 2400 tons of electro waste, 2100 tons of gravel, 840 tons of sand and to liquidate approximately 3200 tons of non-recyclable waste during the whole year. [ABSTRACT FROM AUTHOR]

In modern times, production management must quickly respond to the fluctuations in the demand for production materials by production equipment oriented to different orders. This calls for a reasonable plan for production management. Based on Markov model, this paper explores the demand prediction of production materials, and investigates the simulation of production management. Firstly, the grey system model and the Markov chain model were combined into a hybrid prediction model for the dynamic and time-varying demand for production materials in the production process. Through dynamic scenario analysis, the authors explored the formulation of production management and control strategies under multiple uncertain demands for production materials, and gave the specific analysis process. Multiple performance indices were considered synthetically, the optimization objectives of production control simulation were given under the multiple uncertain demands for production materials, and a solution was put forward for the production control problem. The simulation results verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

The IoT maximizes the information and intelligence of large-scale producers, and greatly improves the supervision quality and efficiency of production lines. Existing research fails to use modern logistics simulation for distributed simulation, verification and analysis of industrial automated production line management (IAPLM). Thus, this paper studies the distributed simulation of IoT-based IAPLM. The time domain, component information and other elements are introduced into the distributed Petri network model to realize the optimization of the logic model of the industrial automation production line. The key points of distributed simulation design of IAPLM are introduced in detail, and the timing design of the production process, the mapping of logical model to distributed simulation platform, the structured processing of models, and the construction of simulation strategies for production equipment control are completed. Experimental results verify the effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

Manufacturing resources are the core resources for intelligent manufacturing enterprises. It is of great practical significance to improve the reliability and stability of production control in a dynamic production environment with long-term frequent disturbances. This paper explores the simulation system design and development for combined service optimization and production control of intelligent manufacturing. After specifying the system architecture, modelling and matching were carried out according to the specific requirements of intelligent manufacturing combined service objects in the production process. Next, a six-tuple was introduced into the service provided by the production control system combined with the Internet of things (IoT), the formal definition was given to the IoT service and intelligent manufacturing combined service, and the key parts were described in detail with the overall service description and combined service description of the six-tuple as examples. Through experiments, the results of the simulation system were outputted. [ABSTRACT FROM AUTHOR]

Using simulation as a tool for production process optimization represents a useful approach to exploring many optimization options which lie ahead on the process improvement path. Previously published research papers report on combining the simulation with another optimization method or a set of manufacturing practices or digital technology. To avoid the complexity of the developed optimization approach in practical application, this paper presents an approach that focuses on grouping the parts first and then simulating the parts group schedule, batch size, and parts interarrival time options to minimize production process cycle time and maximise the output quantity. The developed algorithm was tested with the data from a real case, for the production of the subassembly for the metal frame used in automotive parts logistics. The experimental results show improvements in defined performance parameters for set optimization goal. [ABSTRACT FROM AUTHOR]

The paper presents the use of simulation modelling methods to evaluate the impact of the collaborative workplaces (human-robot collaboration) importance in correlation to the sustainable manufacturing. Based on an example, numerical simulation results of an existing manual assembly workplace and a newly proposed collaborative workplace are presented using production parameters that describe all three key aspects of sustainable manufacturing: economic, social and environmental aspect. A datadriven simulation model was used, mainly using the input parameters of the real-world production system and numerical assumptions obtained from the literature, with the main objective of detailing the impact on the sustainable orientation of the production process. The results presented in the paper demonstrate the high suitability of simulation modelling methods in the evaluation of existing and newly proposed technologies from the sustainable manufacturing point of view. The results demonstrate that collaborative workplaces, if implemented appropriately and using correct input data, are a possible solution that can cope with limited human resources and ensure high production efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the effects of the big five, individual entrepreneurial orientation, love of money, and theory of planned behaviour dimensions on the entrepreneurial attitude and intention among freelancers. The moderating effect of gender in freelancers was also examined. The research was conducted in Western Balkan countries: Bosnia and Herzegovina, Croatia, Montenegro, and Serbia. A total of 318 questionnaires were collected. The influences of the theory of planned behaviour and individual entrepreneurial orientation dimensions are significant and positive. The positive impact of dimension openness is emphasised. Motivation to make money has a strong and positive effect on entrepreneurial attitudes and intentions, especially among men. The desire to achieve freedom through money has a positive impact on entrepreneurial attitudes, but also a negative effect on entrepreneurial intentions. Analytical and graphical modelling of the detected impacts was performed. Based on the real values of the independent variables that apply to a certain freelancer, analytical models can be used to simulate the entrepreneurial attitudes and intentions of that individual. [ABSTRACT FROM AUTHOR]

Rail grinding with abrasive belt is increasingly applied in daily rail maintenance due to its high efficiency and high quality. The contact between rail and abrasive belt largely determines grinding efficiency and grinding quality, but the influences of grinding process and contact wheel’s parameters on the contact behaviour are obscure. To explore the influences, a finite element model of the wheelrail contact was established. The simulation results showed that the grinding angle significantly affected the shape of contact spot. The contact spot gradually became narrower as the grinding angle increased. Similarly, the reduction of the contact wheel radius significantly increased the contact stress. But when the ratio of the thickness of rubber layer to wheel radius increased above 60 %, it had little effect on the size of contact spot and maximum contact stress. This study provides the basis for the selection of grinding process and contact wheel’s parameters. In the actual grinding process, grinding process and contact wheel should be selected according to grinding requirements. (Received in April 2022, accepted in June 2022. This paper was with the authors 2 weeks for 1 revision.) [ABSTRACT FROM AUTHOR]

As intelligent and precision manufacturing becomes the trend of industrial production, it is of practical significance to study the job-shop production control. However, the existing studies have not provided an evaluation mechanism to reasonably measure the control efficiencies of different plans. The desired control objectives are not easily achieved for job-shop production control problems with dynamic changes. Therefore, this paper probes into the dynamic job-shop production control problem based on deep reinforcement learning and rule scheduling. Firstly, a multi-objective optimization model was established for the production control system of dynamic job-shop. Then, deep reinforcement learning was introduced to job-shop production control system to transform the dynamic job-shop production control problem. After that, the authors proposed a dynamic job-shop production control method based on deep reinforcement learning, and explained the collaboration strategy for multiple subsystems. The proposed method was proved effective through experiments. [ABSTRACT FROM AUTHOR]

Blockchain supports free and reliable transactions of the production material supply chain (PMSC). However, few scholars have combined the blockchain with supply chain management. Based on blockchain, this paper explores the collaborative management of material supply chain for production and manufacturing job-shops (PMJs). Specifically, a collaborative management model was constructed, and the execution of the smart contract between PMJ and production material supplier (PMS) was explained. Then, the Stackelberg game between PMJ and PMS in the model was analysed, and the calculation method of the total benefit of PMS and PMJ was derived, under the information sharing mode of the blockchain-based PMSC model. Through trust evaluation, the dishonest companies were identified in the PMSC. To ensure the safe and reliable data sharing between the companies in our model, the probability for the dishonest companies to participate in smart contract was reduced, making it less likely for false shared data to appear in the chain. The effectiveness of the proposed blockchain-based model for the collaborative management of PMSC was proved through simulations. [ABSTRACT FROM AUTHOR]

Double-top-beam support (DTBS) is an important protective device for backfilling mining. Frequent roof movements cause the DTBS to bear dynamic loads, making it prone to instability and damage. The gaps between the supporting parts exacerbate this condition. To solve this problem, we studied the dynamic characteristics of the DTBS with gaps under various impact loads. Firstly, the numerical model of the support was built. The connecting joints of the DTBS were defined with a gap clearance. Then, the attitude and load characteristics of the DTBS were analysed by applying biased, symmetrical, and torsional load to both top beams. The results indicate that the connecting joints at the top beam are more sensitive to the impact loads. When the impact loads appear at the front part, the load of the connecting bar joints increased. The gap size has a minimal effect on the lateral inclination of the DTBS. The biased loading condition plays a crucial role in the deviation of the top beam supporting attitude. Under the same loading condition, the inclination of the rear top beam is much higher than that of the front top beam, with a degree difference of approximately 130 minutes. (Received in March 2023, accepted in May 2023. This paper was with the authors 3 weeks for 2 revisions.) [ABSTRACT FROM AUTHOR]

Given the high prices of machine tools, customers often engage in careful deliberation before placing any orders for machines. The number and size of orders may suddenly change when the demand unexpectedly increases or plummets. This paper proposes the concept of "reservation threshold", which refers to mitigating possible crowding-out by applying advanced capacity for handling potential orders. This threshold also serves as an order entrance control to reduce the number of non-confirmed orders. A simulation model is used to explore the impact of various threshold values on production system profitability. Data abstracted from a representative company are used as a case study. Scenarios for three reservation strategies are examined for negotiation probability distributions. Through numerical experiments, the significance of an appropriate reservation threshold is demonstrated for normal capacity scenarios; the reservation strategy outperforms the no-reservation strategy under conditions of normal and insufficient capacity while the module reservation strategy is the best of the three reservation strategies. [ABSTRACT FROM AUTHOR]

With the continuous growth of the automation level, the production process is featured by multiple stages and process parameters. There is a huge sum of diverse data on automated production. With a low value density, these data come from heterogenous sources, and respond to lots of concurrent processing demands. It is necessary to simulate and optimize the production scheduling of the automated production system. Drawing on the existing research, this paper illustrates the process of multi-stage production scheduling of automated production, and simulates the automated production line on Plant Simulation. The flow of the simulation model was illustrated, the simulation objectives were specified, and the model hypotheses were detailed. From the angle of deterministic simulation modelling, a joint optimization model was established for the multi-stage production scheduling of automated production, and the production task assignment was improved for traditional pull scheduling model to meet the demand of dynamic collaborative demand for machines. The proposed model was proved effective through simulations. [ABSTRACT FROM AUTHOR]

An approach to solving the problem of machining time estimation in production of complex products within CNC machining systems is presented in the paper. Heuristic analysis of the process is used to define the attributes of influence to machining time. For the problem of estimating machining time the following „Neural Computing techniques" are used: Back-Propagation Neural Network, Modular Neural Network, Radial Basis Function Neural Network, General Regression Neural Network and Self-Organizing Map Neural Network. Real data from the technological process obtained by measuring are used to design the model used in investigation. The established model is used to carry out the investigation aimed at learning and testing different algorithms of neural networks and the results are given by the RMS error. The best results in the validation phase were achieved by Modular Neural Network (RMSE: 1.89%) and Back-Propagation Neural Network (RMSE: 2.03%) while the worst results were achieved by Self-Organizing Map Neural Network (RMSE: 10.05%). [ABSTRACT FROM AUTHOR]

In order to study the generation and distribution of plastic zone of cohesive soil foundation with the change of foundation pressure and foundation width, particle image velocimetry testing technology and discrete element method are used to study the dynamic distribution characteristics of plastic zone of cohesive soil, foundation failure mode and corresponding foundation bearing capacity values. By using particle image velocimetry testing technology, the plastic zone of clay under different foundation load is obtained, in which the ultimate foundation bearing capacity can be taken as 120 kPa. The development law of foundation plastic zone simulated by UDEC is highly consistent with that of foundation plastic zone based on PIV test. Through the parameterized numerical simulation test of the foundation plastic zone, this paper discusses the variation law of foundation plastic zone with the changes in the foundation load and the width of foundation, which can be used to study the dynamic development process of plastic zone of the shallow foundation. The research has important guiding significance for evaluating the range of foundation plastic zone in foundation design. [ABSTRACT FROM AUTHOR]

Modelling and simulation (M&S) is one of the fundamental methods of performance analysis. In other words, how well a modeller builds a model is a key point of a successful performance analysis. Before such a performance analysis, a model for prediction should be constructed. There are two types of models: data model and simulation model. Data model represents correlational relationships between one set of data and another. Conversely, simulation model represents causal relationships between a set of controlled inputs and corresponding outputs. This paper identifies the characteristics of each modelling method and presents a cooperative model development process for performance analysis of complex systems. The cooperative method contains conceptual modelling, model classification, and model integration/implementation. The model classification method effectively reflects and maximizes the features compared earlier. Then, they are modelled respectively and integrated. This paper also applies the proposed modelling to develop a model of Hadoop using artificial neural network (ANN) and discrete event systems specification (DEVS). To demonstrate the validity of the case study, it presents experiments to show the possibility of a proposed approach. (Received in July 2019, accepted in October 2019. This paper was with the authors 2 weeks for 1 revision.) [ABSTRACT FROM AUTHOR]

In the era of Industry 4.0 and intelligent manufacturing, accurately predicting and maintaining production line faults is crucial in manufacturing. This study introduces a novel deep learning-based adaptive fault prediction and maintenance strategy, overcoming limitations of traditional statistical and machine learning methods in prediction accuracy and adaptability in complex environments. A new prediction model is developed, incorporating a wide convolutional feature extraction module, a customized gating module, and a multi-layered progressive extraction module. The model's process and parameters, including fault stage division using Wasserstein distance and optimization with L2 regularization and neuron dropout, are detailed. An adaptive maintenance strategy for predictive fault detection is established, enhancing precision in fault prediction and developing more effective maintenance approaches, ultimately boosting production efficiency and reducing operational costs. [ABSTRACT FROM AUTHOR]

The article examines the creation of a Cost Economy Energy Savings Simulation Model (CEESS Model) as an economic scenario generator for energy-independent structures using the Monte Carlo method. The CEESS model is a continuous simulation model created on the ExtendSim simulation system platform. The problem is related to the constantly changing environmental parameters for the purpose of energy security for buildings as modern, energy-independent and self-sufficient systems. In terms of the implementation of the defined part of the research, a logistical approach was applied: system analysis, coordination, algorithm work, planning, efficiency. We define logistics as a system, principle, philosophy of management of flows. The numerous simulation experiments carried out show that the return on investment of the option with an initial investment of 5000 euros is in the range of 2422 to 4978 days, the return on investment of the option with an initial investment of 10000 euros is in the range of 4233 to 7902 days and the return on investment of the option with an initial investment of 15000 euros is in the range of 5691 to 10073 days. [ABSTRACT FROM AUTHOR]

The fourth industrial revolution, or Industry 4.0 (I4.0), originated in German, englobes many innovative features, in order to bring the concept of "smart factories". Moreover, discrete-event simulation (DES) is one of the most important areas involved in this goal. With this in mind, the purpose of this paper is to propose a research and development agenda (R&D) for DES researchers and practitioners, in order to comply with the I4.0 agenda. To achieve this, a literature review (LR) was conducted, in which 45 papers were considered relevant for this research. From their analysis, it was found that: the ability to automatically generate simulation models; the automation of data exchange between manufacturing applications and simulation tools; and visualization features, are the most essential DES features for I4.0. Thereafter, the LR focused on analysing the most recent papers in these areas of simulation, in order to propose a list of R&D items for DES researchers and practitioners. [ABSTRACT FROM AUTHOR]

The production management of hybrid flow shop (HFS) has a great practical significance. Proper production management can improve the machine utilization and shorten the makespan in a complex production control environment. However, the relevant research has not paid enough attention to realistic constraints like multi-period control, and job transport time. To solve the problem, this paper explores the production management of HFS based on improved genetic algorithm (GA). Specifically, several assumptions were proposed for the multi-objective optimization problem of HFS production management, and new constraints like multi-period control, and job transport time were introduced to the problem. Then, the authors established a multi-objective optimization model for HFS production management, and improved the traditional GA to solve the model more rapidly and accurately. The proposed model and algorithm were proved effective through experiments. [ABSTRACT FROM AUTHOR]

In modern manufacturing, dynamic allocation of resources is key to enhancing production efficiency and competitiveness. With the advancement of intelligent manufacturing and Industry 4.0, the manufacturing environment has become increasingly complex and variable, making traditional static resource allocation methods insufficient for practical needs. This paper aims to explore multi-objective optimization methods for dynamic manufacturing resource allocation by constructing a multi-objective optimization model and proposing an improved NSGA-II algorithm to address this issue. The study demonstrates that the improved algorithm significantly enhances population diversity and global search capability, effectively coping with dynamic manufacturing environments to provide efficient and reliable resource allocation solutions. This research not only offers new insights into dynamic resource allocation but also serves as a valuable reference for related fields. [ABSTRACT FROM AUTHOR]

Flexible job shops have difficulties in selecting rescheduling schemes under various disturbances. This paper proposes a rescheduling decision selection method that comprehensively considers production loss cost, completion time, machine load balancing rate, and additional machine energy consumption. First, the G1-improved entropy method and the improved TOPSIS method are combined to evaluate rescheduling schemes. Meanwhile, the proposed method combines subjective and objective factors to provide decision-makers with the optimal rescheduling scheme, leading to higher rationality, practicality, and effectiveness of the rescheduling process. Finally, a case study verifies the applicability of the proposed method in a typical flexible job shop scenario. [ABSTRACT FROM AUTHOR]

Freight transport is a fundamental activity for the economic growth of a country or region, and the transport sector is one of the main contributors to gross domestic product (GDP) measurements. The total tons to be transported per year and transport types must be taken into account by state organisations for infrastructure planning, routes, prices and taxes. Governments make investment decisions according to the size of the freight mobilised per year. Transportation companies should contemplate external and internal variables, for example, fuel prices, distances, environmental impact, among others. Sustainability has become a determining factor in transport companies' decision making. This paper presents a novel study about the factors that affect freight land transport from the sustainability perspective. Then it proposes a conceptual framework to act as a roadmad to build a simulation model of freight land transport by defining the key parameters in economic, social and environmental terms. [ABSTRACT FROM AUTHOR]

To clarify the evacuation bottleneck of air-rail intermodal hub stations and improve the efficiency of personnel evacuation, the smoke spread process and the visibility and temperature changes in the case of fire in an air-rail intermodal hub station in Zhengzhou, Henan, China, were simulated via PyroSim simulation software based on performance-based fire protection design technology. The available safe escape time was obtained, the whole process of safe personnel evacuation was simulated, the bottleneck position in the process of evacuation was revealed, and the time required for safe crowd evacuation in the fire environment was determined. Results show that with a smoke exhaust system, smoke spreads to both sides of the hub station in 270 s, the visibility on both sides is affected, and the safe evacuation conditions fail. When the smoke exhaust system does not function, the available safe escape time is 497 s, and the required safe escape time is 370.5 s. The obtained conclusions provide a decision reference for performance-based fire protection design of air-rail intermodal hub stations. [ABSTRACT FROM AUTHOR]

To address the challenge of high rejection rates due to surface quality defects that are hard to detect with the naked eye, a comprehensive model was developed for detecting such defects and implemented a full-fledged equipment and system for surface quality inspection. Specifically, a targeted comprehensive model was formulated to identify three types of plate and strip surface quality defects. Furthermore, the latest hardware equipment and an advanced unsupervised self-learning algorithm were integrated into the detection system to enhance the identification and classification of these surface quality defects. The results demonstrate an improvement in the comprehensive detection rate and classification accuracy of surface defects from 96 % and 91 % to 98 % and 95 %, respectively. Moreover, the qualified rate of finished products has increased from 94 % to 99 %, leading to improved accuracy in defect detection and a significant decrease in false alarm rates. These findings provide a solid foundation for significantly reducing material waste and enhancing the overall quality of the production process. [ABSTRACT FROM AUTHOR]

The counter jib and rod support are the main stress-bearing parts of crane due to large load. But the long weld seams of their joints produce great residual stress and deformation affecting the welding strength. In order to reduce the residual stress and the deformation simultaneously, an optimal welding procedure was proposed considering the effective length of welding seam. Firstly, a theoretic model of welding seam was built as T-joint of Q355 steel. The accuracy of model was verified by the welding experiments. By numerical simulation, the appropriate welding process parameters were obtained. Four welding procedures were designed to investigate the influence of the welding sequence. Results show that the welding sequence has a great influence on residual stress and deformation of the long welding seam. The welding quality can be improved by segmented welding and simultaneous welding. The optimized welding procedure of long welding seam can reduce the residual stress by 8.04 % and the maximum deformation by 74.1 % considering welding sequence. Therefore, it is recommended in the actual welding process of crane. (Received in April 2022, accepted in June 2022. This paper was with the authors 3 weeks for 1 revision.) [ABSTRACT FROM AUTHOR]

In automotive industries, variable customer needs’ increase the competition amongst enterprises. However, manufacturers are struggling to complete the customer demand on time. This paper presents a case study taken region in the automotive industry in Michigan, USA. It aims to reduce the production delay by stabilizing manufacturing processes that improve production throughput. Many tools are used including project charter, process flow diagram, Arena simulation, design of experiment (DOE), and layered process audit sheet. The project charter is used to represent the problem, objectives, scope, and methodology. The investigation of the system and the possible improvements are performed using Arena simulation along with DOE. Shop-floor data were collected and statistically analysed to model the different processes. Besides, the Ishikawa diagram was used to identify the root causes of the problems. Results show significant improvements. The number of finished products increased from 726 to 14161 units. The average WIP number increased from 4.9543 to 6.3615 units. The variation amongst the workstations’ utilization is reduced. The cycle time decreased from 203.96 to 130.20 sec. (Received in March 2022, accepted in July 2022. This paper was with the authors 3 weeks for 2 revisions.) [ABSTRACT FROM AUTHOR]

Considering problems like product blockage and machine faults in the batch scheduling of product assembly lines, this paper proposes a multi-objective flow shop batch scheduling model taking these problems into account, and by comparing with the traditional flow shop scheduling model, it verifies the feasibility and superiority of this model. The results show that, regarding the product blockage problem, this paper improves the MWH heuristic algorithm, leading to better quality of the initial population produced; and that it also proposes a new ISBOX crossover operator algorithm, which is used in combination with the nondominated solution information to calculate the new solution for offsprings, improving the local search capability of the algorithm. In order to address machine faults, this paper obtains new solutions by optimizing the maximum completion time and the early completion time, takes the new solutions as the initial population, and uses the proposed model to optimize the robustness and stability of the existing algorithm. By comparing the proposed model and the traditional scheduling model in terms of product blockage and machine fault, this paper finds that the proposed algorithm has high local and global convergence, and generates high-quality nondominated solutions. According to the re-scheduling strategy, this algorithm can effectively reduce the effects of product blockage and machine faults on the objective function. [ABSTRACT FROM AUTHOR]

Presented paper is focused on comparison of three types of steel for production of tubes with shaped internal surface for applications in energy producing industry. Simulations were performed in Deform-3D software with usage of finite elements method. Steels 20MnCr5, C10 and 34CrNiMo6 were selected for simulations. Obtained results are showing deformation, stress, strain and temperature during cold drawing of tubes with shaped internal surface and also resulting comparison of three tested materials depending on the course of load during the forming process. As a conclusion of the presented research is comparison of presented three steels according to the simulation results. Presented paper has potential to increase knowledge base in the area of forming tubes with shaped internal surface. Obtained results can contribute to a proper selection of tool material, coatings and process set up for forming process of tubes with shaped internal surface. [ABSTRACT FROM AUTHOR]

This paper makes a systematic analysis of the automotive inbound logistics, and integrates the automotive inbound logistics system and the production system by rationalizing the three main links of the logistics, taking the theory of value chain increment as the guide, and using the idea of station marshalling driving. This paper integrated and optimized three main links of inbound logistics, constructed the optimization mode of automotive inbound logistics driven by station feeding marshalling and its supporting system. In the Work-Station Marshalling-Driven Automotive Inbound Logistics Mode, we construct a mathematical model and design a hybrid genetic algorithm that combines a local search algorithm and a genetic algorithm. And at the end the validity and practicality of this research is demonstrated by real-life examples. [ABSTRACT FROM AUTHOR]

Logistical risks are now significantly more acute due to epidemics, economic recession and local political turmoil. Cross-border logistics risks are particularly prevalent given the large number of participants and the long transport distances involved. This paper develops a system dynamics model to analyse the key factors of cross-border logistics risk. In previous studies, people usually consider the risk factors as many independent individuals. But actually, there is a causal relationship as well as conduction effects between risk factors. Therefore, this paper analyses the relationship between risk factors through qualitative analysis and establishes a system dynamics model to indicate the direction of risk transmission. The rate of risk transmission was analysed using quantitative methods. Finally, this paper conducts simulations using survey data of cross-border e-commerce enterprises in Chengdu, indicating that the industry currently has more prominent customs risks, process risks, and cooperation risks. For these more serious risks, this paper proposes corresponding prevention and control measures. [ABSTRACT FROM AUTHOR]

This paper is focused on streamlining the activity of the homogeneous production processes which form the production logistics of a particular extraction operation. The efficient extraction of millions of tonnes of raw materials presents a requirement for the correct use of the means of transport, machinery and equipment involved in the extraction of raw materials, with an economic, social, technical and ecological impact. The extraction operation studied is performed in a quarry for the extraction of limestone, which is used as input material for the production of various types of building materials. The extracted raw material gradually passes through the chain of extraction - loading - transport - unloading - crushing to the actual processing in the building materials plant. The results of the solution show that the maximum effective use of the operation of the defined system can be achieved with 27 means of transport and 4 loaders, while the utilization of workplaces in extraction operation workplaces is close to 100 % during the defined time of operation. [ABSTRACT FROM AUTHOR]