Research on Processes Simulation and Reconfiguration for Piston Production Lines

Zhou, Jun; Zhao, Shu-chun; Li, Puhong; Zhou, Hao; Zhang, Qingyuan; Shang, Zihe

doi:10.1109/iccms.2009.13

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…Number of operators, level of inventory and operational factors as shown in following Table 1 are collected. Construction of simulation model from the data collected is for the experimentation purpose. Simulation method is extensively used by industry to test different scenarios, model any abnormal situation and drive recommendation based on the results once the desired target is attained in the model (De Carlo, Arleo & Tucci, 2014;Zhou, Zhao, Li, Zhou, Zhang & Shang, 2009). Simulation-based framework has also been used to model the market behavior and production system so that demand and execution uncertainty could be considered as well as for the identification of production waste such as waiting, work in progress, inventories and transportation (Badiger & Gandhinathan, 2008;Heilala, Vatanen, Tonteri, Montonen, Lind, Johansson et al, 2008;Ponsignon & Mönch, 2014).…”

Section: Methodsmentioning

confidence: 99%

Novel availability and performance ratio for internal transportation and manufacturing processes in job shop company

Perumal

Teoh

Ito

2020

JIEM

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Purpose: Purpose of this study includes the quantification of the impact of transportation efficiency onto the workstations the transportation serves in term of throughput and total lead time elapsed by product. Besides, it aims to synchronize the capacity available among workstations throughout a production line by studying the upper limit of throughput could be afforded by each workstation as well as their connection with each other. This study is also done on the purpose of promoting fulfillment of customer demand at shorter delivery time and minimal equipment utilization. Investigation on implementation of Overall Equipment Effectiveness (OEE) in an aerospace part-manufacturing company is studied to track out the potential opportunities to be improved.Design/methodology/approach: Site observation is conducted on all the five manufacturing workstations in the aforementioned aerospace part manufacturing company. Time data of both automated processes and manual processes are collected and they are used to construct simulation model. From that, various scenarios of transportation efficiency are simulated in Experiment 1. In addition, Experiment 2 is also set to examine the maximum capacity of each workstation. All of these are to highlight the relationship between workstation and processes and to verify the condition of imbalanced capacity among workstations in the company. In short, this has necessitated the integration of workstation and transportation activities within the company. These are followed by proposal of measures to quantify the wastes identified.Findings: The paper finds that implementation of OEE alone does not consider the reasonability of customer demand fulfillment. The results show that both transportation efficiency and imbalanced capacity throughout production system are not emphasized by OEE implementation in the case company. Therefore, responsibility of all workstations and transportation process in delivering demand on time are quantified. Transportation process which serves as the connectors of manufacturing processes is quantified and monitored by proposed Transportation Measure (TM) whereas workstations are measured using novel availability and performance ratio.Research limitations/implications: Future research should be conducted to examine the impact of other station within a company such as warehouse and logistic department to the performance of equipment and materials in manufacturing workstation. Besides, the material availability as well as the skills or performance of man power could be further incorporated into the measures to consider all the entities involved in manufacturing processes.Practical implications: The proposed availability and performance ratio for both transportation and manufacturing processes, which are related to each other, help in promoting better effectiveness of production system in terms of production amount and lead time. Besides, reasonable utilization equipment and minimal consumption of material are incorporated in the measures to promote Lean way in fulfilling customer demand. The effectiveness of entire production line is examined as a unity with joint responsibility under varying transportation efficiency and cycle time of each workstation. Both measures could be implemented together to optimize the production system and quantify the hidden wastes which are neglected in the OEE implementation.Originality/value: The novel availability and performance ratio are proposed to consider customer demand, historical equipment utilization and Takt time of each workstation to examine the possibility and reasonability of demand fulfillment. This prevents both over-processing and overproduction issues which are invisible in OEE. Furthermore, delay propagation throughout production system and interrelationship between processes are quantified under transportation measure. Other novelty of the paper is that it monitors the waiting time and lead time spent in each workstation at the same time considering utilization of workstation. The proposed Transportation Measure (TM) aims to reduce the queue length and waiting time at destination workstation at minimal utilization of forklift. It also promotes less capacity investment in transportation and prioritizes its scheduling according to urgency of destination workstation.

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Section: Methodsmentioning

confidence: 99%

Novel availability and performance ratio for internal transportation and manufacturing processes in job shop company

Perumal

Teoh

Ito

2020

JIEM

View full text Add to dashboard Cite

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“…Dynamic programming as a new and important operations research branch, by the American mathematician Bellman (R Bellman), who proposed a multi-stage decision-making process to solve optimization problems in a way [1][2][3][4]. Dynamic programming has become a modern enterprise management is an important decision-making methods, successfully solved the problem of optimal path, resource allocation, production planning and inventory, investment and loading, sorting and production process issues such as optimal control.…”

Section: Introductionmentioning

confidence: 99%

Study on Modeling and Improving on the Production and Service Operations Management of Enterprise

Wang

Cai

Jiang

et al. 2014

AMM

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The optimization problems about production and service operations management was proposed in the paper. Dynamic programming was introduced to optimize production and service operations. Meanwhile, the concept and principle of dynamic programming was introduced and the multi-stage decision was analyzed. Then, the model was established and the model solution is given. In the end, the example provided demonstrates the application in the service operations management and it was proved that the methods proposed efficiency to solve the optimization problems about production and service operations management.

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An integrated simulation–optimization study for consolidating production lines in a configure-to-order production environment

Aqlan

Lam

Ramakrishnan

2014

International Journal of Production Economics

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Research on Processes Simulation and Reconfiguration for Piston Production Lines

Cited by 3 publications

References 3 publications

Novel availability and performance ratio for internal transportation and manufacturing processes in job shop company

Novel availability and performance ratio for internal transportation and manufacturing processes in job shop company

Study on Modeling and Improving on the Production and Service Operations Management of Enterprise

An integrated simulation–optimization study for consolidating production lines in a configure-to-order production environment

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