Loading policies in cellular manufacturing systems with remainder cell

Renna, Paolo; Ambrico, Michele

doi:10.1080/0951192x.2011.570791

Cited by 6 publications

(4 citation statements)

References 14 publications

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“…Renna (2016) explored the effect of a hybrid preventive maintenance policy in a manufacturing system with reminder cell, and the maintenance policy is a tradeoff between the preventive and corrective approach. Renna and Ambrico (2011) proposed the cell-loading approaches in a manufacturing system including dedicated cells and a remainder cell. The remainder cell consists of machines which can manufacture all part families.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation optimization of operator allocation problem with learning effects and server breakdown under uncertainty

Heydarian

Jolai

2018

Production & Manufacturing Research

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This paper investigates the operator allocation problem with learning effects and server breakdown in cellular manufacturing systems (CMSs) using fuzzy computer simulation and response surface methodology (RSM). The primary contribution of this study is incorporating combined server breakdowns and learning effects in CMS under uncertainty. Machine breakdowns of all the machines as well as the probability related to each entity should be delivered in good order are considered. Also, previous studies did not consider fuzzy simulation and RSM to deal with environmental and data uncertainty in operator allocation problems. The superiority of the presented model, in comparison with the traditional one, is shown according to the number of required iterations. The proposed simulation model is run in uncertain state to obtain the total processing time. RSM algorithm identifies a fitted function in terms of the value of allocated capital to each server and total processing time. This is a practical approach for decisionmakers of all Cellular Manufacturing Systems.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation optimization of operator allocation problem with learning effects and server breakdown under uncertainty

Heydarian

Jolai

2018

Production & Manufacturing Research

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“…The moving average is computed on 10 unit time. Moreover, the following environmental conditions are considered: 1) the processing time is extracted by a uniform distribution [2,8] in order to consider the case of variable process time (case 2). 2) The introduction of the machine failures with the following parameters: Mean Time Between Failures (MTBF) following a normal distribution N(500,50) for all machines and the Mean Time To Repair (MTTR) of 15 unit times (case 3).…”

Section: Simulation Environmentmentioning

confidence: 99%

“…In literature several alternatives have been proposed as virtual manufacturing cells [3], fractal cells, ( [4] and [5]), holonic cells [6] and remainder cells' introduction in the design of CMSs [7]. Some studies investigated the loading policies in cellular manufacturing systems with reminder cell [8], the performance of classical cellular manufacturing systems compared to fractal cells and remainder cells [9], the design and reconfiguration of CMSs with reconfigurable machines to handle the turbulent market conditions [10]. The research proposed in this paper concerns the virtual cellular manufacturing systems (VCMS).…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Design Policies in Virtual Cellular Manufacturing Systems by Multi-Domain Simulation Environment

Renna

2014

AMM

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In today’s competitive market, customer demand is characterized by high fluctuations and it is more difficult to forecast. Therefore, the classical cellular manufacturing systems need to be revised in order to stay competitive. Among the different approaches to support the cellular manufacturing systems, the concept of virtual cellular manufacturing systems can improve the performance in turbulent environment. This paper proposes two policies to support the problem of the reconfiguration of machines in a virtual cellular manufacturing system. The policies proposed are tested developing a multi-domain simulation environment in ExtendSim®. The experiments conducted show how the proposed approach improves the performance of the manufacturing systems especially when some disturbances occur as demand fluctuations, machine failures and processing time are uncertain.

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“…Therefore, the traditional line balancing method is unsuitable for the one-piece flow production system (Go¨kc¸en et al 2010, Lu et al 2011, Renna and Ambrico 2011. Afterwards, the line balance and the machine sharing can be considered and improved.…”

Section: Construct the Continuous Flow Within A Cellmentioning

confidence: 99%

Design of one-piece flow production system with mixed flows: a timed process flow diagram-based approach

Wang

et al. 2012

International Journal of Computer Integrated Manufacturing

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Nowadays, shorter product life cycles and increased product varieties make it difficult to produce some products on traditional production lines. The best that can be done is to manufacture them in one-piece flow production systems. However, the conventional quantitative and qualitative production system design techniques focus on the part of the complex production system (i.e. machining cell, assembly line) rather than the entire production system. Therefore, they are not the best choice for creating the one-piece flow production system with mixed flows. In this article, a systematic procedure based on the timed process flow diagram (TPFD) for design one-piece flow production system is represented. The main idea of the proposed method involves two steps: one is to design and describe the initial production system based on TPFD, that is, define the production family, construct the manufacturing cell and handle the continuous flow within a cell; another is to improve the initial production system according to the critical path of TPFD and focus on reducing the lead time (LT) of product in the complex production system with mixed flows and synchronising the whole production system in a systematic way. One case in real life was studied to evaluate the workability and efficiency of our proposed method in the complex one-piece flow production system.

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Loading policies in cellular manufacturing systems with remainder cell

Cited by 6 publications

References 14 publications

Simulation optimization of operator allocation problem with learning effects and server breakdown under uncertainty

Simulation optimization of operator allocation problem with learning effects and server breakdown under uncertainty

Design Policies in Virtual Cellular Manufacturing Systems by Multi-Domain Simulation Environment

Design of one-piece flow production system with mixed flows: a timed process flow diagram-based approach

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