Productivity Improvement Strategies Using Simulation in Offshore Plant Construction

Back, Myung Gi; Woo, Jong Hun; Lee, Philippe; Shin, Jong Gye

doi:10.5957/jspd.33.2.150016

Cited by 6 publications

(2 citation statements)

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“…Subsequently, researchers studied other production planning methods and algorithms by taking into account the characteristics of the shipbuilding project process [38,39], and some systems were developed to effectively implement a production planning process [40,41]. In recent years, the production process planning and management for ships with complex equipment and technology were studied by the Markov decision processes [42], and then a simulation model was established [43]. Meanwhile, the related research on supply chain management was carried out for the shipbuilding industry [44].…”

Section: Shipbuilding Project Planning and Schedulingmentioning

confidence: 99%

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

Mao

Guo

et al. 2020

Symmetry

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In the current distributed manufacturing environment, more extensive enterprise cooperation is an effective means for shipbuilding companies to increase the competitiveness. However, considering the project scale and the uneven production capacity between the collaborative enterprises, a key issue for shipbuilding companies is to effectively combine the product-oriented project tasks and the specialized production-oriented plants. Due to information privatization, the decision-making process of project planning and scheduling is distributed and symmetric. Existing project scheduling methods and collaboration mechanisms in the shipbuilding industry are somehow inefficient. The aim of the research is to provide an assistant decision-making method to support effective task dispatching and multi-party cooperation for better utilization of the distributed resources and to help project managers control the shipbuilding process. The article initially establishes an agent-based complex shipbuilding project collaborative planning and symmetric scheduling framework, simulating the distributed collaborative decision-making process and bridging the multi-project planning with the individual project scheduling in much detail, which fills the research gap. A negotiation method based on iterative combination auction (ICA) is further proposed to solve the integration problem of project planning and task scheduling, and an illustrative example is conducted to demonstrate the effectiveness and rationality of the methods. Finally, an application case using a prototype system on shipbuilding projects collaborative planning and scheduling will be reported as a result.

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Section: Shipbuilding Project Planning and Schedulingmentioning

confidence: 99%

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

Mao

Guo

et al. 2020

Symmetry

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“…Owing to changes in the global manufacturing environment, the shipbuilding industry currently faces challenges of survival and sustainability [1]. The global economic recession has induced shrinking international trade, while marine resource development projects are also decreasing or being canceled owing to declining oil prices, which are definitely unfavorable conditions for the shipbuilding and marine industry [2]. Analysts predict that it will be difficult to return to the early boom period of orders for ships and offshore plants, such as around 2010, which is referred to as the "super cycle" in the shipbuilding industry.…”

Section: Introductionmentioning

confidence: 99%

Assessment Framework of Smart Shipyard Maturity Level via Data Envelopment Analysis

et al. 2021

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The fourth industrial revolution (“Industry 4.0”) has caused an escalating need for smart technologies in manufacturing industries. Companies are examining various cutting-edge technologies to realize smart manufacturing and construct smart factories and are devoting efforts to improve their maturity level. However, productivity improvement is rarely achieved because of the large variety of new technologies and their wide range of applications; thus, elaborately setting improvement goals and plans are seldom accomplished. Fortunately, many researchers have presented guidelines for diagnosing the smartness maturity level and systematic directions to improve it, for the eventual improvement of productivity. However, most research has focused on mass production industries wherein the overall smartness maturity level is already high (e.g., high-level automation). These studies thus have limited applicability to the shipbuilding industry, which is basically a built-to-order industry. In this study, through a technical demand survey of the shipbuilding industry and an investigation of existing smart manufacturing and smart factories, the keywords of connectivity, automation, and intelligence were derived and based on these keywords, we developed a new diagnostic framework for smart shipyard maturity level assessment. The framework was applied to eight shipyards in South Korea to diagnose their smartness maturity level, and a data envelopment analysis (DEA) was performed to confirm the usefulness of the diagnosis results. By comparing the DEA models, the results with the smart level as an input represents the actual efficiency of shipyards better than the results of conventional models.

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Integrating occupational health and safety into plant simulation

Pons

Pearse

2020

Safety Science

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Productivity Improvement Strategies Using Simulation in Offshore Plant Construction

Cited by 6 publications

References 0 publications

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

Research on Collaborative Planning and Symmetric Scheduling for Parallel Shipbuilding Projects in the Open Distributed Manufacturing Environment

Assessment Framework of Smart Shipyard Maturity Level via Data Envelopment Analysis

Integrating occupational health and safety into plant simulation

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