Using workflow for reconfigurable simulation-based planning and scheduling system

Lee, Ho Yeoul; Choi, Byoung Kyu

doi:10.1080/0951192x.2010.542180

Cited by 6 publications

(3 citation statements)

References 20 publications

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“…They applied them to the modelling of a U-shaped line, in order to show the appositeness of the developed model. Lee and Choi designed a modular reconfigurable simulation-based framework for the creation of planning and scheduling systems within a manufacturing context [13]. Applications of modular simulation models to remanufacturing systems are not being developed so far.…”

Section: Literature Reviewmentioning

confidence: 99%

Modularization in material flow simulation for managing production releases in remanufacturing

et al. 2017

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Remanufacturing is recognized as a major circular economy option to recover and upgrade functions from post-use products. However, the inefficiencies associated with operations, mainly due to the uncertainty and variability of material flows and product conditions, undermine the growth of remanufacturing. With the objective of supporting the design and management of more proficient and robust remanufacturing processes, this paper proposes a generic and reconfigurable simulation model of remanufacturing systems. The developed model relies upon a modular framework that enables the user to handle multiple process settings and production control policies, among which token-based policies. Customizable to the characteristics of the process under analysis, this model can support logistics performance evaluation of different production control policies, thus enabling the selection of the optimal policy in specific business contexts. The proposed model is applied to a real remanufacturing environment in order to validate and demonstrate its applicability and benefits in the industrial settings.

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Section: Literature Reviewmentioning

confidence: 99%

Modularization in material flow simulation for managing production releases in remanufacturing

et al. 2017

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“…a workflow management system (WfMS), that thoroughly defines and automatically executes workflows in order to manage the actual flow of work so that the right work is done at the right time with the right information by the right person in the organization (WfMC 1995). Also, the application of this technology can be extended to the development of a reconfigurable information system that enables rapid implementation and maintenance (Lee and Choi 2011). In this paper, the workflow technology is not limited to the sharing of the future visibility; but also used for developing the outpatient operation management system that can be extended to work for other configurations of outpatient departments.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Simulation-based operation management of outpatient departments in university hospitals

Choi¹,

Kang²,

Kong³

et al. 2013

2013 Winter Simulations Conference (WSC)

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Recently, the growth of outpatient clinic capacity has not matched the increasing demand on outpatient clinics, which has led to long waiting times for patients and overtime work for clinic staff. This has three significant negative effects on patients and staff: (1) patients' distrust of the procedures for treating outpatients increases, (2) nurses' stress from patient complaints increases, and (3) doctors' pressure to shorten treatment times while maintaining high levels of service quality increases. Presented in this paper is a simulation-based operation management method that provides the stakeholders with future visibility in outpatient departments. The future visibility is obtained from the current situation of the outpatient department using a simulation-based scheduling system and is shared by a business process management system that informs patients of their expected waiting time in order to lower the workload and pressure on clinic staff and to allow staff to manage exceptions proactively.

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“…The second modeling option is simulation, which has grown up into a very common tool to analyze large problems and, more specifically, scheduling problems both in the industrial 6–8 and in the service sectors. 9,10 Its boost lately relates both to its extraordinary representation capabilities, including logic and randomness, as well as the utilization during the optimization stage of the so-called simulation-optimization (SO) methodologies.…”

Section: Introductionmentioning

confidence: 99%

meSO: simulation optimization using a multicriteria process capability index and evolutionary algorithms

Otamendi

2012

SIMULATION

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A successful implementation of a simulation-optimization (SO) methodology is presented. Based on evolutionary algorithms with a multicriteria fitness function, the new SO is used to developed weekly schedules at a ship building factory that manufactures around 60 jobs per week. Simulation modeling is used to account for randomness on the input data, as well as to correctly abstract the complex operations carried out in the real system. A variant of genetic algorithms is used to search for the appropriate schedule. Its fitness function is a multicriteria process capability index that aggregates three individual criteria, namely, makespan, line blockage and idleness of resources. The index is based on the satisfaction of thresholds for each and every criterion, thresholds that are tightened as improved schedules are found. The thresholds are also used to reject non-promising alternatives without having to perform the same number of runs as for the candidates that stand out for implementation. The name of the methodology is meSO: multicriteria evolutionary SO.

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Using workflow for reconfigurable simulation-based planning and scheduling system

Cited by 6 publications

References 20 publications

Modularization in material flow simulation for managing production releases in remanufacturing

Modularization in material flow simulation for managing production releases in remanufacturing

Simulation-based operation management of outpatient departments in university hospitals

meSO: simulation optimization using a multicriteria process capability index and evolutionary algorithms

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