Application of Pull Concept-based Lean Production System in the Ship Building Industry

Hassan, Khairul; Kajiwara, Hiroyuki

doi:10.5957/jspd.29.3.120021

Cited by 12 publications

(3 citation statements)

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“…The cost (man hour) control models developed by Niksa Fafandjel et al (2010) and Emblemsvag (2014) etc. created studies that contributed to the work of Hassan & Kajiwara (2013); and studies on the running distance optimization of the crane were done by Roh & Lee (2010) etc. They aimed to apply the lean production and operational research methods in shipbuilding production management by achieving balancing production via means of management, reducing the waste of resources, and shortening the shipbuilding cycle time of product construction to achieve efficiency improvement.…”

Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Efficiency Structure Analysis Model of Shipbuilding Based on Driving Factors: The Case of Chinese Shipyard

Xue¹,

Shi²,

Dashuang³

et al. 2020

JSS

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The purpose of this paper is to build an efficiency evaluation model based on efficiency drivers. Building technique, resource ability and management level are the three main driving factors in production efficiency of shipbuilding. Two-stage internal production efficiency structure analysis model (ESAM) firstly decomposes the shipbuilding system efficiency into three dimensions of subsystem efficiency structures to express the driving effect of the three driving factors of technique, operation and management. Secondly, ESAM uses system efficiency function and dimension structure efficiency function to express the relationships between the efficiency of each level and its subordinate efficiency. The contribution of subsystems to system efficiency is represented by the regression coefficient while the driving relationship between the efficiency of the subsystems and the efficiency of the system is expressed by the moving average trend curves of the system efficiency and the structural efficiency of each dimension. The empirical analysis shows that the case shipyard inner production is inefficient, which implies that most Chinese shipyards may be in the same condition, or even worse. It also shows that operation efficiency has the greatest driving effect on shipbuilding system efficiency while the driving effect of technique efficiency is not obvious, which means that improving management efficiency and technique efficiency should be the main direction taken to improve Chinese shipbuilding efficiency.

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Section: Literature Reviewmentioning

confidence: 99%

Two-Stage Efficiency Structure Analysis Model of Shipbuilding Based on Driving Factors: The Case of Chinese Shipyard

Xue¹,

Shi²,

Dashuang³

et al. 2020

JSS

View full text Add to dashboard Cite

show abstract

“…The Lean term comprises the establishment of a culture of continual improvement and organizational learning [14]. At the operational level, it reduces unnecessary production time, materials and manufacturing efforts, thus reducing the cost by reducing waste [15]. There are obstacles that must be taken into account when seeking the implementation of this methodology, namely the human factor often brings the rejection of change by employees and that can cast doubt to the implementation of Lean [16].…”

Section: Lean Productionmentioning

confidence: 99%

Regression Models for Lean Production

Bragança

Portela

Santos

2017

Advances in Intelligent Systems and Computing

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Data mining models are an excellent tool to help companies that live from the sales of items they produce because it allows the company to optimize its production and reduce costs, for example in storage. When these models are combined with Lean Production, it becomes easier to remove waste and optimize industrial production. This project is based on the phases of the methodology CRISP-DM, and aims to reduce and, if possible, eliminate wastage. The following methods: average, mean and standard deviation, quartiles and Sturges rule regression, were techniques applied to this data to determine which one is the model is less likely to make mistakes, in other words, meaning that the model did correctly predict the target. Most common metrics used at the statistical level, which had already been proven to have good results in similar studies. After performing the tests, the M4 model is what is less likely to make mistakes in terms of regression with a RAE of 21,33%.

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“…Most new PCS's (7 out 1 Introduction Production Control Systems (PCS) are a key factor for effective manufacturing systems as they regulate the information and materials flows through the factory (Masin, Herer, and Dar-El 2005;Karrer, Alicke, and Günther 2012). Therefore, the choice of an appropriate PCS is an important success factor for any organization (Hassan and Kajiwara 2013). Consequently, many different PCS's emerged.…”

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confidence: 99%

Systematic review and discussion of production control systems that emerged between 1999 and 2018

Bagni

Filho

Thürer

et al. 2020

Production Planning & Control

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Application of Pull Concept-based Lean Production System in the Ship Building Industry

Cited by 12 publications

References 0 publications

Two-Stage Efficiency Structure Analysis Model of Shipbuilding Based on Driving Factors: The Case of Chinese Shipyard

Two-Stage Efficiency Structure Analysis Model of Shipbuilding Based on Driving Factors: The Case of Chinese Shipyard

Regression Models for Lean Production

Systematic review and discussion of production control systems that emerged between 1999 and 2018

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