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The purpose of this paper is to introduce a method for modelling the multi-state repairable systems subject to stochastic degradation processes by using the coloured stochastic Petri nets (CSPN). The method is a compact and flexible Petri nets model for multi-state repairable systems and offers an alternative to the combinatory of Markov graphs.

The method is grounded on specific theorems used to design an algorithm for systematic construction of multi-state repairable systems models, whatever is their size.

Stop and constraint functions were derived from these theorems and allow to considering k-out-of-n structure systems and to identifying the minimal cut sets, useful to monitoring the states evolution of the system.

The properties of this model will be studied, and new investigations will help to demonstrate the feasibility of the approach in real world, and more complex structure will be considered.

The simulation models based on CSPN can be used as a tool by maintenance decision makers, for prediction of the effectiveness of maintenance strategies.

The proposed approach and model provide an efficient tool for advanced investigations on the development and implementation of maintenance policies and strategies in real life.

The purpose of this paper is to demonstrate the use of Petri nets in a job shop setup for the improvement in the utilization of machines.

The study discusses concepts such as reachable state, token and matrix equations set, and demonstrates the improvements in machines’ utilization in a job shop. It makes use of algorithms to generate reachable markings to obtain utilization. The study not only describes the application of theory, but also extends the body of knowledge on Petri nets and job shops.

In this study, machines’ utilization has been studied in a job shop with six machines and eight products. The study finds that substantial utilization improvement in job shop set up can be obtained through the application of Petri nets. The study also exposes that Petri nets are mostly used for machines, jobs and tools scheduling problems, but its use in machines’ utilization is neglected. The framework and application presented here along with generalizable findings, is the first to report about machine utilization improvement in job shop manufacturing environment.

Job shops are characterized by high unit production cost, low investments, low volume and high variety, complex flows, flexible and skilled work force, general purpose machines, high material handling; resulting in poor utilization of machines. Therefore, the findings of this study can help in reducing such costs through better machine utilization. This can help in increasing the competitiveness of the companies.

The contribution of study lies in investigating and improving stage wise utilization in a job shop setup. It has never been reported before.

The purpose of this paper is to present a Petri net (PN) model based on assembly plan is presented for modeling a flexible assembly system (FAS) configuration, determining an optimal work‐in‐process (WIP), lead time, throughput, and utilization of each station.

PN model is developed for design, analysis, and performance evaluation of a FAS, keeping in view the assembly line balancing. PN is optimized using weighted WIP. The throughput is bounded by the utilization of the bottleneck machines.

The PN optimization gives minimum WIP corresponding to the maximum production rate. Minimum WIP leads to minimum lead time. The weighted arcs make the model simple and reduce the optimized number of kanbans. Moreover, the PN model pushes more inventory to the initial assembly phase. This reduces the total cost of the WIP.

In the proposed PN model, the transportation times are included in the transitions times. In the future research, the proposed model can be extended for inclusion of transportation times for AGVs.

Using the PN model, the assembly manager may design, analyze, evaluate, and even optimize the layout of the assembly system for minimum WIP, maximum throughput, and reduced lead time. The determination of the total WIP, total number of stations in the assembly system, and the number of servers at each station may be helpful in factory floor management. The same cycle time is managed at each assembly station for the purpose of line balancing. It may result in the highest efficiency and the shortest idling time along with ease of management and supervision.

This paper presents a new PN model for the design and performance evaluation of a dual kanban FAS.

Predicting the final status of an ongoing process or a subsequent activity in a process is an important aspect of process management. Semi-structured business processes cannot be predicted by precise and mathematical methods. Therefore, artificial intelligence is one of the successful methods. This study aims to propose a method that is a combination of deep learning methods, in particular, the recurrent neural network and Markov chain.

The proposed method applies the BestFirst algorithm for the search section and the Cfssubseteval algorithm for the feature comparison section. This study focuses on the prediction systems of social insurance and tries to present a method that is less costly in providing real-world results based on the past history of an event.

The proposed method is simulated with real data obtained from Iranian Social Security Organization, and the results demonstrate that using the proposed method increases the memory utilization slightly more than the Markov method; however, the CPU usage time has dramatically decreased in comparison with the Markov method and the recurrent neural network and has, therefore, significantly increased the accuracy and efficiency.

This research tries to provide an approach capable of producing the findings closer to the real world with fewer time and processing overheads, given the previous records of an event and the prediction systems of social insurance.

The purpose of this paper is to present a new generic Petri net (PN) model based on assembly plan for assembly sequence optimization. The model aims to allow modeling the flexible assembly system (FAS) configuration, determining the optimal work in process, lead time, throughput, and utilization of each station. Moreover, it aims to show assembly features (AFs) as being useful in assembly sequence planning.

Sophisticated knowledge of AFs is used to get very few feasible assembly sequences (ASs) rather than all possible ASs for a product. A PN model is developed to find out the near optimal assembly sequence out of the sequences obtained from the AF knowledge. It is also used for design and performance evaluation of FAS. Multiple optimization criteria are used for assembly sequence optimization, keeping in view the line balancing. The PN is optimized using weighted‐WIP when the throughput is bounded by the utilization of the bottleneck machines.

The results achieved from the example show a considerable reduction in the number of feasible ASs for a product. The PN optimization gives minimum WIP corresponding to the maximum production rate. Moreover, the PN model pushes more inventories to the initial assembly phase.

The proposed PN can be easily extended for inclusion of dual kanban, where the managers may adjust the number of kanban cards as per the requirement.

Managers may use the concept of multiple AFs in order to design and operate robot assembly that will result in more efficient sequence planning. Using the PN model, the assembly manager may design, analyze, evaluate, and even optimize the layout of the FAS for minimum WIP, maximum throughput, and reduced lead time. The determination of total WIP, total number of stations in the assembly line, and the number of servers at each station may be helpful in the factory floor management. Line balancing may result in the highest efficiency and the shortest idling time along with ease of management and supervision.

This paper provides a clear insight into how a large reduction in the number of feasible ASs for a product can be obtained using the knowledge of AFs. It also presents a new PN model used for assembly sequence optimization and design and performance analysis of FAS.

Modeling and system performance analysis play an important role in the planning of air traffic system. In particular, this paper aims to concentrate on the modeling and the performance evaluation of air transportation system.

It has shown that system matrices inherent in the airspace network can be acquired based on the service times of flights. This paper deals with a logical modeling which can avoid temporal synchronization conflict of resources. As a result, a class of queuing system is investigated to obtain a representation of the airspace network dynamics using dioid model.

The analysis of the air traffic system is conducted by solving the system state model. This indicates that it is feasible to use eigenvalues of system model for acquiring characteristics of the considered air transport systems.

The departure scheduling prototype presented in this paper can offer air traffic controller a decision support tool to build optimal departure sequences for aircraft.

The properties of max-plus algebra described allow us to apply linear algebra concepts like eigenvalue and eigenvectors to obtain a solution to the air traffic system being modeled. By solving and analyzing the dioid model, this paper evaluated some performance measures of airspace network.

End‐of‐life (EOL) products have become a major environmental issue among countries and manufacturers. This is due to the growing number of EOL products and their hazardous contents. Many collection strategies and pilot projects have been conducted to manage EOL products, especially Waste Electrical and Electronics equipments (WEEEs). However, as characteristics of a population are different to one another, a customized collection strategy is required. The purpose of this paper is to find an effective collection strategy which considers cost and environmental impact simultaneously.

This paper presents an integrated collection strategy which combines a Fuzzy Colored Petri Net forecasting method and collection network model to collect EOL products. Colored Petri Net is used in modeling the integrated collection strategy. To test the collection strategy, a case study on mobile phone collection in Australia is presented.

The integrated collection strategy developed in this paper finds that by providing demographic data and historical sales of a relevant product in a certain location, the best strategy to collect EOL products in that location can be determined. This paper finds that the best strategy that suits one location might be different to other locations.

This paper presents a model which provides a customized collection strategy that follows the characteristics of a population. This strategy allows government organizations or manufacturers to simulate the strategies to collect EOL products in different locations.

On the basis of analyzing the drawbacks of the existing concurrent engineering (CE), a new concept of agile concurrent engineering (ACE) characterized by the agile teams is presented. The organization method of the agile teams is discussed. The implementation and quantitative process modeling problems of ACE are dealt with. Contrasted with the existent CE, ACE puts the problems of resource sharing into special consideration. Its realization requires as little reform of the current organizational structures of enterprises as possible. ACE is more applicable to the product development in firms, especially in medium‐sized or small companies.

This paper aims to deal with the problems of failure dependence and common cause failure (CCF) that arise in reliability analysis of complex systems.

Firstly, a dynamic fault tree (DFT) is used to capture the dynamic failure behaviours and converted into an equivalent generalized stochastic petri net (GSPN) for quantitative analysis. Secondly, an efficient decomposition and aggregation (EDA) theory is combined with GSPN to deal with the CCF problem, which exists in redundant systems. Finally, Birnbaum importance measure (BIM) is calculated based on the EDA approach and GSPN model, and it is used to take decisions for system improvement and fault diagnosis.

In this paper, a new reliability evaluation method for dynamic systems subject to CCF is presented based on the DFT analysis and the GSPN model. The GSPN model is easy to capture dynamic failure behaviours of complex systems, and the movement of tokens in the GSPN model represent the changes in the state of the systems. The proposed method takes advantage of the GSPN model and incorporates the EDA method into the GSPN, which simplifies the reliability analysis process. Meanwhile, simulation results under different conditions show that CCF has made a considerable impact on reliability analysis for complex systems, which indicates that the CCF should not be ignored in reliability analysis.

The proposed method combines the EDA theory with the GSPN model to improve the efficiency of the reliability analysis.

Information distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.

A simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.

The bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.

Information sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.

Colored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.