Modelling and simulation of re-entrant flow shop scheduling: An application in semiconductor manufacturing

El-Khouly, Ingy A.; El-Kilany, Khaled S.; El-Sayed, Aziz E.

doi:10.1109/iccie.2009.5223754

Cited by 13 publications

(9 citation statements)

References 10 publications

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“…Constraint (4) ensures that each operation can only be processed on one machine at the corresponding stage. Constraints (5)- (7) ensure that each machine processes at most one operation simultaneously. Constraints (8) and (9) specify the starting and ending time of O jk .…”

Section: Mathematical Modelmentioning

confidence: 99%

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Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Geng

Dai

et al. 2020

Complexity

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Re-entrant hybrid flow shop scheduling problem (RHFSP) is widely used in industries. However, little attention is paid to energy consumption cost with the raise of green manufacturing concept. is paper proposes an improved multiobjective ant lion optimization (IMOALO) algorithm to solve the RHFSP with the objectives of minimizing the makespan and energy consumption cost under Time-of-Use (TOU) electricity tariffs. A right-shift operation is then used to adjust the starting time of operations by avoiding the period of high electricity price to reduce the energy consumption cost as far as possible. e experimental results show that IMOALO algorithm is superior to multiobjective ant lion optimization (MOALO) algorithm, NSGA-II, and MOPSO in terms of the convergence, dominance, and diversity of nondominated solutions. e proposed model can make enterprises avoid high price period reasonably, transfer power load, and reduce the energy consumption cost effectively. Meanwhile, parameter analysis indicates that the period of TOU electricity tariffs and energy efficiency of machines have great impact on the scheduling results.

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Section: Mathematical Modelmentioning

confidence: 99%

“…In practice, the total tardiness objective is treated as constraints, so the problem is converted into single objective. El-Khouly et al [7] used Lagrange decomposition to optimize the RSP aiming at minimizing the total tardiness. Wu et al [8] studied RSP with learning effects, aiming at minimizing the makespan.…”

Section: Introductionmentioning

confidence: 99%

Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Geng

Dai

et al. 2020

Complexity

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“…Heuristic techniques such as dispatching rules and constructive heuristics have also been applied to the re-entrant flow shop scheduling problem. The dispatching rules are applied in the semiconductor industries by testing various experiments for the simulation models (Cigolini et al, 1999;El-Khouly et al, 2009;Perkins and Kumar, 1995). Though these heuristic methods produce good quality solutions, they are not extensively used during the period of 2000-2007 as the running time are often large and increase rapidly with size of the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

Lin

Lee

2013

Engineering Applications of Artificial Intelligence

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Re-Entrant Flowshop Scheduling Problem (RFSP) is regarded as NP-hard problem and attracted the attention of both researchers and industry. Current approach attempts to minimize the makespan of RFSP without considering the resources constraints and interdependency of re-entrant probability. This paper proposed Multilevel Genetic Algorithm (GA) by including the co-related re-entrant possibility and production mode in multi-level chromosome encoding. Repair operator is incorporated in the Multi-level genetic algorithm so as to revise the infeasible solution by resolving the resource conflict. With the objectives of minimizing the makespan, Multi-level Genetic Algorithm (GA) was proposed and ANOVA is used to fine tune the parameter setting of GA. The experiment shows that the proposed approach is more effective to find the near-optimal schedule than the simulated annealing algorithm for both small-size problem and large-size problem.

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“…Duenyas, 1994;El-Khouly, El-Kilany, & El-Sayed, 2009;Prakash & Chin, 2014;Ryan, Baynat, & Choobineh, 2000;Ryan & Vorasayan, 2005;Satyam & Krishnamurthy, 2008; investigated the behaviour and the effect of the work-in-process inventory limit of CONWIP). The assumptions that production authorisation cards are the same in single and multi-product lean manufacturing environments were prevalent in these studies, resulting in the dedication of production authorisation cards to a part-type in these studies.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of multi-product lean manufacturing systems with setup and erratic demand

Onyeocha

Khoury²,

Geraghty

2015

Computers & Industrial Engineering

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Modelling and simulation of re-entrant flow shop scheduling: An application in semiconductor manufacturing

Cited by 13 publications

References 10 publications

Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Bi-Objective Re-Entrant Hybrid Flow Shop Scheduling considering Energy Consumption Cost under Time-of-Use Electricity Tariffs

Multi-level genetic algorithm for the resource-constrained re-entrant scheduling problem in the flow shop

Evaluation of multi-product lean manufacturing systems with setup and erratic demand

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