Development of Integrated Production Scheduling System in the Process Industry

Omar, Mohamed K.; Suppiah, Yasothei; Teo, Siew Chein

doi:10.3844/jcssp.2005.395.399

Cited by 2 publications

(2 citation statements)

References 12 publications

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“…Emami-Mehrgani et al (2011) discussed that industry strives to cut down on production costs and optimize profit through operating methods consistent with various legal requirements. In this regard, numerous of scholars have made attempts to schedule via divergent methods including classical& fuzzy logic scheduling (Tzimopoulos et al, 2008) genetic algorithm (Taghavifard et al, 2009;Gao and Liu, 2007), neural network artificial (Venkatachalam et al, 2008), fuzzy logic (Omar, 2007) and programming model (Chen, 2010), real time scheduling algorithm (Ahmad and Othman, 2010), Petri nets (Ghoul et al, 2007) and hierarchical scheduling (Omar et al, 2005) so on.…”

Section: Introductionmentioning

confidence: 99%

Case Study of the Optimizing the Automotive Manufacturing Systems Efficiency via Applying New Method of Scheduling

Nojabaei

Franchetti

2014

American Journal of Engineering and Applied Sciences

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Efficiency is becoming a pivotal aspect in each manufacturing system and scheduling plays a crucial role in sustaining it. The applicability of distributed computing to coordinate and execute jobs has been investigated in the past literature. Moreover, it is significant that even for sensitive industrial systems the only criterion of allocating jobs to appropriate machines is the FIFO policy. On the other flip, many researchers are of the opinion that the main reason behind failing to provide fairness in distributed systems is considering the only criterion of time stamp to judge upon and form the queue of jobs with the aim of allocating those jobs to the machines. In order to increase the efficiency of sensitive industrial system, this study takes into consideration of three criteria of each job including priority, time action and time stamp. The methodology adopted by this study is definition of job scheduler and positioning jobs in temporary queue and sorting via developing bubble sort. In sorting algorithm criterion of priority, time action should be considered besides time stamp to recognize the tense jobs for processing earlier. To evaluate this algorithm first a numerical test case (simulation) is programmed and then the case study performing in order to optimize efficiency of applying this method in real manufacturing system. Eventually the results of this study provided evidence on that the rate of efficiency is increased.

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Section: Introductionmentioning

confidence: 99%

Case Study of the Optimizing the Automotive Manufacturing Systems Efficiency via Applying New Method of Scheduling

Nojabaei

Franchetti

2014

American Journal of Engineering and Applied Sciences

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“…Moreover, Mahamed K.Omar, et.al, [54] introduced a three-level hierarchical production planning and scheduling approach to cope with planning problem in resin factory. In this research, planning decisions are divided into three levels which each level is strongly related to the others.…”

Section: An Integrated Problemmentioning

confidence: 99%

Marker planning for fabric cutting with sewing schedule constraint in mass customization context

Puasakul

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The objective of this research is to develop heuristics for marker planning problem within a sewing schedule under mass customization production context. In this context, a number of sizes and an amount of demand in each size are varied in a wider range than a mass production system but with lesser total demand. The proposed problem is divided into two subproblems. The first subproblem corresponds with the cost dimension of a marker planning. Hence, the objective is to minimize the total cost related to a number of markers and excessive units. The second subproblem aims to integrate a sewing schedule into marker planning. Therefore, the objective is to minimize a work-in-process inventory workload. The initial solution from the first heuristic is determined by an LP relaxation of marker planning. Then, it is improved by a greedy-based algorithm. This algorithm focuses on reducing an unnecessary plies and adjusting marker patterns. Furthermore, initial solutions are randomized to avoid getting stuck with a local optimum. The second heuristic further improve a first heuristic’s solution by focusing on rearranging marker patterns in order to correspond with a sewing schedule. To measure performance of the proposed heuristics, the first heuristic is tested with many problems. For small-and medium-sized problems, the heuristic can reach to the optimal solutions in all problems while with large-sized problems, heuristic solutions are better than solutions from GA which can reach to optimal solutions as well. The second heuristic is tested with large-sized problems. The second heuristic can perform better than GA method.

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Development of Integrated Production Scheduling System in the Process Industry

Cited by 2 publications

References 12 publications

Case Study of the Optimizing the Automotive Manufacturing Systems Efficiency via Applying New Method of Scheduling

Case Study of the Optimizing the Automotive Manufacturing Systems Efficiency via Applying New Method of Scheduling

Marker planning for fabric cutting with sewing schedule constraint in mass customization context

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