The development of modelling tools to improve energy efficiency in manufacturing processes and systems

Research output: Contribution to journalReview article

2 Citations (Scopus)

Abstract

With increasing governmental pressures to reduce energy consumption, manufacturing companies are faced with the challenge of reducing energy consumption whilst maintaining or increasing profits and productivity. Computational modelling is a powerful tool for energy analysis within the manufacturing industry as an effective decision making technique in order to optimise throughput, effectively plan and manage operations, reduce bottlenecks and test various scenarios. This study reviewed methodologies and frameworks developed for analysing energy consumption on a machine process level. Multi-level holistic analysis allowing for consideration of individual machines, the manufacturing process chain and built environment, with both discrete event and continuous based simulation are also presented. The requirement of a complete, high accuracy computational model is highlighted in order to understand the interaction between all relevant material, energy and resource flows. Challenges associated with achieving a holistic simulation of the manufacturing facility with all relevant parameters is presented, along with areas for further development. Furthermore, the development of Industry 4.0 is reviewed, along with new and emerging technologies allowing for increased automation, connectivity and flexibility within manufacturing, as well as visual techniques to provide further understanding and clarity of manufacturing processes such as digital twins, virtual and augmented reality.

LanguageEnglish
Pages95-105
Number of pages11
JournalJournal of Manufacturing Systems
Volume51
DOIs
Publication statusPublished - 30 Apr 2019

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Energy efficiency
Energy utilization
Industry
Augmented reality
Virtual reality
Profitability
Automation
Productivity
Decision making
Throughput

Keywords

  • digital twinning
  • discrete event simulation
  • energy modelling
  • industry 4.0
  • manufacturing energy analysis

Cite this

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title = "The development of modelling tools to improve energy efficiency in manufacturing processes and systems",
abstract = "With increasing governmental pressures to reduce energy consumption, manufacturing companies are faced with the challenge of reducing energy consumption whilst maintaining or increasing profits and productivity. Computational modelling is a powerful tool for energy analysis within the manufacturing industry as an effective decision making technique in order to optimise throughput, effectively plan and manage operations, reduce bottlenecks and test various scenarios. This study reviewed methodologies and frameworks developed for analysing energy consumption on a machine process level. Multi-level holistic analysis allowing for consideration of individual machines, the manufacturing process chain and built environment, with both discrete event and continuous based simulation are also presented. The requirement of a complete, high accuracy computational model is highlighted in order to understand the interaction between all relevant material, energy and resource flows. Challenges associated with achieving a holistic simulation of the manufacturing facility with all relevant parameters is presented, along with areas for further development. Furthermore, the development of Industry 4.0 is reviewed, along with new and emerging technologies allowing for increased automation, connectivity and flexibility within manufacturing, as well as visual techniques to provide further understanding and clarity of manufacturing processes such as digital twins, virtual and augmented reality.",
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N2 - With increasing governmental pressures to reduce energy consumption, manufacturing companies are faced with the challenge of reducing energy consumption whilst maintaining or increasing profits and productivity. Computational modelling is a powerful tool for energy analysis within the manufacturing industry as an effective decision making technique in order to optimise throughput, effectively plan and manage operations, reduce bottlenecks and test various scenarios. This study reviewed methodologies and frameworks developed for analysing energy consumption on a machine process level. Multi-level holistic analysis allowing for consideration of individual machines, the manufacturing process chain and built environment, with both discrete event and continuous based simulation are also presented. The requirement of a complete, high accuracy computational model is highlighted in order to understand the interaction between all relevant material, energy and resource flows. Challenges associated with achieving a holistic simulation of the manufacturing facility with all relevant parameters is presented, along with areas for further development. Furthermore, the development of Industry 4.0 is reviewed, along with new and emerging technologies allowing for increased automation, connectivity and flexibility within manufacturing, as well as visual techniques to provide further understanding and clarity of manufacturing processes such as digital twins, virtual and augmented reality.

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KW - discrete event simulation

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