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The purpose of this paper is to examine the issues affecting end of life (EOL) management of flexible packaging. It focuses on Sustainable Solid Waste Management by using multi-criteria decision making, analytic network process (ANP), and Strengths, Weaknesses, Opportunities, and Threats (SWOT).

Data were collected from 33 expert stakeholders, though a series of interviews and questionnaires. The subject seven aspects were applied from integrated sustainable waste management with 19 sub-criteria identified. Criteria were prioritized by using ANP and SWOT to the internal and external environments of organizations directly responsible for waste management.

The five most important factors in the management of flexible packaging waste include: techniques for waste management, material and design, management support, legislation and rule, and environmental care and environmental health, respectively. Solutions addressing flexible packaging waste were identified, including reuse and recycle, waste to energy, biopolymers, new innovative materials and material recovery.

Data were derived from the national authorities and large companies. The findings may not represent local authorities and small-scale manufacturers. Future research should be conducted, in order to investigate and focus around small manufacturing enterprises.

The findings provide a strategic framework for policy makers and industrial manufacturers. The benefits of this will enable them to address flexible packaging waste, by using qualitative and quantitative criteria.

This is the first paper developing a multi-criteria assessment model to specifically manage EOL flexible packaging, a possible pioneering piece of research in this field.

A major factor to the success of flexible manufacturing systems (FMSs) is their ability to transport work pieces between different workstations. FMS have now become more advanced and material‐handling systems have become progressively more sophisticated, it is not exceptional to have automated steering of tools to workstations as well. Such system design will improve the tool‐handling capability and the system productivity while holding tool cost to a minimum. Tool cost could represent as much as 25 percent of the operating cost. The purpose of this paper is to propose a new colored Petri net (CPN)‐based approach to the design and development of a tool sharing control system that is intended to help use of the proper and minimal number of tools for a manufacturing system.

A new black token timed PN model is first developed, to reduce the complexity of the graphical representation a new CPN model is developed. The new CPN model also allows to find the optimal sequence. The optimal sequence has no effect on the work in process (WIP) but it influences the number of tools used in the system. The main input to the PN model for a manufacturing system is the process plan. Next, all the invariants and total number of possible elementary circuits are determined using the Integrated Net Analyzer (INA) software. Output from the INA software is exported to the Excel spreadsheet. The Excel spreadsheet can be designed to calculate the total number of tokens, processing time, cycle time, etc. of each elementary circuit. Subsequently, the constraints used in Lingo will be created according to critical circuit rules. Finally, linear programming (LP) technique is used to optimize the WIP and tool inventory. Lingo software is used for the LP, the constraints from the Excel sheet will be the input data to the Lingo program, and based on those constraints the Lingo will provide the optimal values for the desired parameters. The output from Lingo will be used to recalculate the cycle time of each elementary circuit in the Excel sheet. The system is then analyzed before and after the implementation of the CPN model.

A new CPN model based on tool‐sharing philosophy for an FMS with N part types and M stations is proposed.

The paper presents a new CPN‐based approach to the design and development of a tool sharing control system, that is, intended to help use of the proper and minimal number of tools for a manufacturing system. The new CPN model also allows to find the optimal sequence. The idea is new and pure and has not been presented before using the methodology adopted in this paper.

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.

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.

This paper presents a computational framework that combines both fuzzy sets and analytical hierarchy process (AHP) for selecting the best‐ranked flexible manufacturing system from a number of feasible alternatives. Fuzzy sets are employed to recognize the selection criteria as linguistic variables rather than numerical ones, which, in turn, makes the framework quite user‐friendly. AHP is used to determine the due weight of the selection criteria, in accordance with their relative importance. In total, 14 criteria are considered, grouping them into flexibility, cost, productivity, and risk. The criteria under the first three groups are independent (i.e. their own fuzzy sets evaluate them) and the criteria under risk are indirectly evaluated by using the fuzzy sets of the criteria under flexibility. The proposed framework is implemented by developing an expert system called FmsExpert, using Borland C++. The performance of this system is also demonstrated by using an example.

This paper presents a new generic Petri net (PN) model for design and performance evaluation of a flexible assembly system (FAS) and disassembly system (DAS) with dual kanban. The architectural design of the model is derived from a generic bill of materials (BOMs) in the FAS, a reverse BOM in the DAS and the process plan in the case of flexible manufacturing system (FMS). Integration of FMS, FAS and DAS by developing a new generic PN model with the pull system is introduced. Analysis and performance evaluation of the new model based on invariant analysis and linear programming are also introduced. The method will be illustrated by a small case study.

The purpose of this paper is to propose a new generic hybrid Petri Net (PN) model combined with the lowest makespan cut (LMC) for job shop scheduling problems in mold manufacturing to minimize the makespan of the mold part manufacture schedule.

The LMC algorithm finds a solution close to the optimal solution. The searching of the LMC algorithm starts from the lowest estimated makespan (lowest makespan). Almost all of the lowest makespans (LM) are infeasible makespans. A shifting percentage (SP) is added to the LM to obtain the shifting makespan (SM). The SM is compared with the completion time computed from the reachability tree of the Petri Net (PN) model. If the completion time is greater than the SM, the corresponding branch is cut from the reachability graph, and the SM will be compared with another branch from the reachability tree. There are two scenarios. In the first scenario, there is no feasible solution resulting from the comparison of the completion time and the SM, because the SM is lower than all of the feasible solutions. Therefore, the SP is used to increase the SM. On the contrary, in the second scenario, there is a feasible solution: the SP is used to reduce the SM. In the first scenario, a makespan that is lower than the optimal makespan is found. In the second scenario, a makespan that is greater than the optimal makespan is found. After getting close to bounds of the optimal makespan, the least makespan found in the bounds is the best solution.

The integration of the Petri Net (PN) model and the LMC algorithm can help to improve the production efficiency. In a case study, the proposed algorithm is being compared with other heuristical methods which are practical examples of mold makespans based on the shortest and the longest processing times. The schedule or the sequence obtained by the proposed algorithm is 30% less than the other methods.

This research will consider scheduling multiple mold. The mold design and the mold testing phase are not considered.

The time to produce a mold is very important. Reducing the mold production time will provide more time for mold assembly and testing. The aim of LMC algorithm is minimize the makespan. The time to produce a mold is reduced by finding the best sequence of the jobs and machines.

This paper proposes the new generic hybrid Petri Net model combined with LMC for job shop scheduling problem in the case of mold making shop to optimize the makespan of mold parts scheduling.

Service supplier selection is a multi-criteria decision-making (MCDM) problem assuming a strategic role for the competitiveness of high-tech manufacturing companies. Nevertheless, especially for service quality evaluation, there is little empirical evidence of the practical usefulness of MCDM methodologies. Aiming to cover this gap between theoretical approaches and empirical applications, the purpose of this paper is to propose a fuzzy extended analytic hierarchy process (FEAHP) approach for service supplier evaluation.

A hybrid approach which combines some of the strengths of the analytic hierarchy process (AHP) and of the fuzzy set theory is presented, as organized into five steps. A case study is used to evaluate the applicability in a real company context.

The usability of the approach is demonstrated in an aerospace company for solving the supplier selection problem of a business software whose applications are still in infancy: a Test Data Management System (TDMS). The illustrative application contains both “general” criteria to be used for other service supplier selection contexts as well as service-specific criteria related to software selection.

Even if the application regards the selection of a software supplier, the methodology can be generically extended to other services’ selection in complex manufacturing industries through the personalization of some criteria.

Implications can be derived both for business managers involved into the decision-making process and for suppliers identifying the most promising features of software quality.

The originality consists in the combination into a hybrid approach of the strong points of the AHP with the fuzzy set; the inclusion of multiple perspectives of decision criteria for service supplier selection, basically the “software product” and “supplier” ones; a real empirical application to test and demonstrate the efficacy and the practical utility of the proposed approach.

The purpose of this paper is to summarize and analyze what is known regarding activity-based costing (ABC) applications in the context of supply chain management (SCM). The authors present a reference framework for practical implications and areas for future research in intra-firm and inter-organizational environments.

The findings underlie a systematic review methodology. Research gaps and guidance for further publications are derived from the reference framework based on ABC and SCM literature.

The review illustrates four main areas for further research: determination of the role of management accounting in SCM (including supply chain finance), integration of time-driven ABC with radio frequency identification (RFID) technology and automatic data collection, analysis of inter-organizational management tools in supply chains in multiple negotiation rounds, and standardization of cost accounting data in supply chains.

The review provides practitioners with three main recommendations: ABC applications require a solid data basis, organizational readiness, commitment from senior management, and an ABC management philosophy; open book accounting for inter-organizational cost information-sharing purposes needs institutional arrangements and economic incentive systems; and sharing costs and benefits among supply chain members requires a change of managers’ mind-set.

This paper reveals practical implications and provides new directions for research based on the reference framework. The paper contributes to the interdisciplinary topic between SCM and management accounting by providing a structured overview of 87 peer-reviewed articles from 1992 to 2016.