A research on problems of mixed-line production and the re-scheduling

Huang, H.-H.; Pei, Wen; Wu, Horng-Huei; May, Ming-Der

doi:10.1016/j.rcim.2012.04.014

Cited by 16 publications

(4 citation statements)

References 5 publications

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“…Wang et al established a Petri net based real-time model for hybrid flow shops to satisfy the small-batch customised production [32]. Huang et al discussed the re-scheduling problems of a mixed-line flow shop and a drum-buffer-rope technique is applied to minimise the longest tardiness for the customers' orders [33]. The research articles above studied the scheduling problem in customised production scenarios with some of them being the mixed-flow shop scenario.…”

Section: Related Workmentioning

confidence: 99%

Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop

Peng

Zhang

et al. 2018

Energies

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To meet the increasingly diversified demand of customers, more mixed-flow shops are employed. The flexibility of mixed-flow shops increases the difficulty of scheduling. In this paper, a mixed-flow shop scheduling approach (MFSS) is proposed to minimise the energy consumption and tardiness fine (TF) of production with a special focus on non-processing energy (NPE) reduction. The proposed approach consists of two parts: firstly, a mathematic model is developed to describe how NPE and TF can be determined with a specific schedule; then, a multi-objective evolutionary algorithm with multi-chromosomes (MCEAs) is developed to obtain the optimal solutions considering the NPE-TF trade-offs. A deterministic search method with boundary (DSB) and a non-dominated sorting genetic algorithm (NSGA) are employed to validate the developed MCEA. Finally, a case study on an extrusion die mixed-flow shop is performed to demonstrate the proposed approach in industrial practice. Compared with three traditional scheduling approaches, the better performance of the MFSS in terms of computational time and solution quality could be demonstrated.

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Section: Related Workmentioning

confidence: 99%

Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop

Peng

Zhang

et al. 2018

Energies

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“…Melouk et al [23] propose a simulation optimization-based decision support system for steel manufacturing where an optimizer, OptQuest TM , sends potentially beneficial process modifications a simulation model to investigate their performance of the system. Through a case study of TFT-LCD manufacturing system, Huang et al [24] develop a simulation model to solve the re-scheduling problems in flow shop mixed-lines. Using computer simulation, Altuntas and Selim [25] evaluate and compare several new weighted association rule-based data mining approaches for facility layout problem.…”

Section: Background Of the Researchmentioning

confidence: 99%

Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry)

Saidabad¹,

Taghizadeh²

2015

AJCM

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Using the accurate methods and tools for evaluation of function in different areas is of great importance. In recent years, much more studies have been done on the nature and methodology of function evaluation in organizations and its improvement. This study aimed to evaluate and improve the function of production line through computer simulation in one of the iron foundries in Iran. For this purpose, at first data has been gathered on the basis of timing with chronometer for each one of the production line machineries and using this data, distribution functions governing the activity cycle of each one of these machineries have been determined; and then, using the required gathered data for computer simulation (taking the advantage of "ED" simulation software), a model was simulated to introduce the current situation of production line and the validity of simulated model was measured on the basis of production rate. And then, considering the criteria such as the production rate, average waiting time, machine utilization coefficient, production yield, production cost, production income and the production time production line function was evaluated. Finally, applying amendment changes on the simulated model improved model was offered.

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“…Huang et al [6] used Flexsim simulation tool to establish and solve rescheduling problems under a flow-shop mixed-line production planning. Da-wei and Jian-guo [7] used Flexsim for simulating the planning and construction of highway bus terminal program dynamically.…”

Section: B Simulation Modelmentioning

confidence: 99%

Simulation based optimization approach to solve a maintenance process problem

Lahiani

Mhamedi

Hani

et al. 2014

2014 International Conference on Control, Decision and Information Technologies (CoDIT)

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In this paper, a simulation based optimization method is introduced. A combined simulation and Non Dominated Sorting Genetic Algorithm-II (NSGA-II) optimization engine is developed to solve a maintenance process problem for an industrial case. The coupling is used in order to optimize the performances of the simulation model representing a maintenance process by choosing the best queues' scheduling policy. Our simulation model is performed using FLEXSIM software. NSGA-II model is implemented using C# language, because it ensures exchanges between FLEXSIM software and Ms Excel. The NSGA-II and simulation models operate in parallel over time with interactions. The aim of this paper is to propose an original approach for reorganizing the maintenance process using simulation based optimization approaches.

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A research on problems of mixed-line production and the re-scheduling

Cited by 16 publications

References 5 publications

Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop

Minimising Non-Processing Energy Consumption and Tardiness Fines in a Mixed-Flow Shop

Performance and Improvement of Production Line Function Using Computer Simulation (Case Study: An Iron Foundry)

Simulation based optimization approach to solve a maintenance process problem

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