Performance evaluation of manufacturing systems based on dependability management indicators—case study: chemical industry

Rezaie, Kamran; Dehghanbaghi, M.; Ebrahimipour, V.

doi:10.1007/s00170-008-1726-8

Cited by 10 publications

(5 citation statements)

References 19 publications

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“…Koren and Shpitalni [10] examined the relationship between configuration design and reliability, productivity, quality, scalability, and cost analysis. In another study [20], availability, reliability, and maintenance analysis of a reconfigurable manufacturing system was performed. However, the diagnostics-based analysis of RMS was not performed in different phases of production.…”

Section: B Diagnostic Of Rmsmentioning

confidence: 99%

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Problem-Specific Heuristics for Diagnosability and Inventory Analysis in a Reconfigurable Manufacturing System

Khan

2022

IEEE Access

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Reconfigurable manufacturing systems are complex systems that are prone to malfunctions and performance decay. Thus, such systems need to be safeguarded against quality issues and decline in production efficiency to ensure the optimal health of machines. The product quality and health of a reconfigurable manufacturing system can be analyzed by using the diagnosability characteristic. This study examines the diagnosability characteristic in a multi-stage reconfigurable manufacturing system. The aim is to understand the impact of time-based diagnostics on the functionality performance of a reconfigurable manufacturing system and the level of inventory used during production. The diagnosability is analyzed regarding product variation and system diagnosability. A mathematical model is proposed, and it is subsequently applied in deterministic and stochastic settings. The deterministic setting is examined through a set of two problem-specific heuristics. The stochastic setting, subject to the gamma process, is examined by using a simulation-based optimization approach. The results suggest that the use of line replacement units can restore a reconfigurable system to optimal functionality, reduce the level of inventory, and complete production in minimum time at the expense of additional cost. Finally, a conclusion and future research avenues are provided.

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Section: B Diagnostic Of Rmsmentioning

confidence: 99%

“…As per the relationships given in eq. (18)(19)(20)(21), the functionality of reconfigurable machines starts producing failed units once the threshold is crossed. Accordingly, in the absence of the distinguishability phase, this threshold is crossed once the detectability phase is elapsed.…”

Section: B Simulation-based Optimization (Sbo) For Stochastic Settingsmentioning

confidence: 99%

Problem-Specific Heuristics for Diagnosability and Inventory Analysis in a Reconfigurable Manufacturing System

Khan

2022

IEEE Access

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“…In this equation, θ represents the DEA efficiency scores for both CCR and BCC models of the manufacturers in the year 2015/2016. The efficiency drivers can include number of outlets, firm nationality, ownership type, mergers and acquisition and experience Gandhi and Shankar, 2014;Glancey, 1998;Rezaie et al, 2009;Thomas et al, 1998;Uyar et al, 2013;Ramanathan, 2008, 2009). The variables in the DEA model have been selected from balance sheets, as well as, profit and loss statement.…”

Section: Environmental Factorsmentioning

confidence: 99%

Operational efficiency of plastic producing firms in Iran: a DEA approach

Ghondaghsaz

Kordnaeij

Delkhah

2018

BIJ

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Purpose Firms are working in a complex environment in which the updated information increase the pace of precise decision making and reduce the risk of wrong decisions. Therefore, discovering firms’ performance is a major issue. The purpose of this paper is to evaluate the efficiency of Iranian plastic producing companies by using data envelopment analysis (DEA). It also discovers various drivers that significantly affect the efficiency of enterprises. Design/methodology/approach The authors studied a sample of 17 manufacturing firms to examine the relative efficiency of companies. They, then, evaluated the effects of efficiency drivers and used two methods for these purposes: DEA and bootstrapped Tobit regression model. Findings The study has shown that two manufacturing firms out of selected 17 are efficient under the Charnes, Cooper, and Rhodes model. Also, nine out of 17 plastic producing companies are productive under the Banker, Charnes, and Cooper model. The results of Tobit regression shows that only two efficiency drivers out of four have a significant positive influence on the efficiency of plastic producing firms. Research limitations/implications Considering one industry and country limits the generalizability of the results provided. Besides, data availability has limited the analysis in some parts, particularly in bootstrapped Tobit regression. Practical implications The authors listed this section into benchmarking and strategical management; more importantly, the suggestions for improving the chemical industry and its future evolution are presented. Originality/value The paper is classified into two issues: the efficiency of plastic producing firms in Iran and evaluating the reason for inefficiency, apart from internal managerial procedures.

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“…This becomes a legitimate problem because perception gap self-evidently relates to supply chain performance and especially the level of cohesiveness and integration. Performance measurement is an essential concept in SCM, and is used not only for supplier evaluation, but also for supplier selection [11][12][13][14]. However, there does not exist a research that frames and measures the perception gap regarding the importance of the various performance criteria.…”

Section: Introductionmentioning

confidence: 99%

Modelling the supply chain perception gaps

Lü

Ertek

Betts

2013

Int J Adv Manuf Technol

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This study applies the research of perception gap analysis to supply chain integration and develops a generic model, the 3-Level Gaps Model, with the goal of contributing to harmonization and integration in the supply chain. The model suggests that significant perception gaps may exist among supply chain members with regards to the importance of different performance criteria. The concept of the model is conceived through an empirical and inductive approach, com-bining the research discipline of supply chain relationship and perception gap analysis. First hand data has been collected through a survey across a key buyer in the motor insurance industry and its eight suppliers. Rigorous statistical analysis testified the research hypotheses, which in turn verified the validity and relevance of the developed 3-Level Gaps Model. The research reveals the significant existence of supply chain perception gaps at all three levels as defined, which could be the root causes to underperformed supply chain.

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Performance evaluation of manufacturing systems based on dependability management indicators—case study: chemical industry

Cited by 10 publications

References 19 publications

Problem-Specific Heuristics for Diagnosability and Inventory Analysis in a Reconfigurable Manufacturing System

Problem-Specific Heuristics for Diagnosability and Inventory Analysis in a Reconfigurable Manufacturing System

Operational efficiency of plastic producing firms in Iran: a DEA approach

Modelling the supply chain perception gaps

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