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Multi-objective opt...
Multi-objective optimisation of tool indexing problem : a mathematical model and a modified genetic algorithm
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- Amouzgar, Kaveh, 1980- (författare)
- Uppsala universitet,Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Division of Industrial Engineering and Management, Uppsala University,Produktion och Automatiseringsteknik (PAT), Production and Automation Engineering,Industriell teknik,University of Skövde, Skövde, Sweden
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- Nourmohammadi, Amir (författare)
- Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Produktion och Automatiseringsteknik (PAT), Production and Automation Engineering,University of Skövde, Skövde, Sweden
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- Ng, Amos H. C., 1970- (författare)
- Uppsala universitet,Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Division of Industrial Engineering and Management, Uppsala University,Produktion och Automatiseringsteknik (PAT), Production and Automation Engineering,Industriell teknik,University of Skövde, Skövde, Sweden
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(creator_code:org_t)
- 2021-03-13
- 2021
- Engelska.
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Ingår i: International Journal of Production Research. - : Taylor & Francis Group. - 0020-7543 .- 1366-588X. ; 59:12, s. 3572-3590
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Abstract
Ämnesord
Stäng
- Machining process efficiencies can be improved by minimising the non-machining time, thereby resulting in short operation cycles. In automatic-machining centres, this is realised via optimum cutting tool allocation on turret-magazine indices – the “tool-indexing problem”. Extant literature simplifies TIP as a single-objective optimisation problem by considering minimisation of only the tool-indexing time. In contrast, this study aims to address the multi-objective optimisation tool indexing problem (MOOTIP) by identifying changes that must be made to current industrial settings as an additional objective. Furthermore, tool duplicates and lifespan have been considered. In addition, a novel mathematical model is proposed for solving MOOTIP. Given the complexity of the problem, the authors suggest the use of a modified strength Pareto evolutionary algorithm combined with a customised environment-selection mechanism. The proposed approach attained a uniform distribution of solutions to realise the above objectives. Additionally, a customised solution representation was developed along with corresponding genetic operators to ensure the feasibility of solutions obtained. Results obtained in this study demonstrate the realization of not only a significant (70%) reduction in non-machining time but also a set of tradeoff solutions for decision makers to manage their tools more efficiently compared to current practices.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik -- Produktionsteknik, arbetsvetenskap och ergonomi (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering -- Production Engineering, Human Work Science and Ergonomics (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Maskinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Mechanical Engineering (hsv//eng)
Nyckelord
- Tool indexing
- genetic algorithm
- non-machining time
- multi-objective optimisation
- SPEA2
- mathematical model
- Production and Automation Engineering
- Produktion och automatiseringsteknik
- VF-KDO
- VF-KDO
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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