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Performance evaluation of machining strategy for engine-block manufacturing
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology. KTH. (Manufacturing and Metrology Systems)ORCID iD: 0000-0002-8597-2604
KTH, School of Industrial Engineering and Management (ITM).
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology. KTH, School of Industrial Engineering and Management (ITM), Centres, Design and Management of Manufacturing Systems, DMMS.ORCID iD: 0000-0001-9185-4607
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Machine and Process Technology.
2015 (English)In: Performance evaluation of machining strategy for engine-block manufacturing, ISSN 1895-7595, Vol. 15, no 4, p. 81-102Article in journal (Refereed) Accepted
Abstract [en]

This paper will introduce a novel methodology for the performance evaluation of machining strategies of engine block manufacturing. The manufacturing of engine components is vital to the automotive and vehicle manufacturing industries. Machining is critical processes in the production of these parts. To survive and excel in the competitive manufacturing environment, companies need to improve as well as update their machining processes and evaluate the performance of their machining lines. Moreover, the lines and processes have to be robust in handling different sources of variation over time that include such examples as demand fluctuations, work-piece materials or even any changes in design specifications. A system dynamics modelling and simulation approach has been deployed to develop a methodology that captures how machining system parameters from the machining process are interacted with each other, how these connections drive performance and how new targets affect process and machine tool parameters through time. The developed model could provide an insight of how to select the crucial machining system parameters and to identify the effect of those parameters on the output of the system. In response to such an analysis, this paper provides (offers) a framework to examine machining strategies and has presented model that is useful as a decision support system for the evaluation and selection of machining strategies. Here a system dynamics methodology for modelling is applied to the milling operation and the model is based on an actual case study from the engine-block manufacturing industry.

Place, publisher, year, edition, pages
2015. Vol. 15, no 4, p. 81-102
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-229289OAI: oai:DiVA.org:kth-229289DiVA, id: diva2:1212185
Note

QC 20180604

Available from: 2018-06-01 Created: 2018-06-01 Last updated: 2018-06-04Bibliographically approved
In thesis
1. Manufacturing Dynamics and Performance Evaluation
Open this publication in new window or tab >>Manufacturing Dynamics and Performance Evaluation
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Manufacturing companies are striving to remain competitive in the market and maintain their economic growth and productivity. Uncertainties regarding the changes in product demand, workpiece material, product design, and technological advancement, have imposed pressure on manufacturing systems. Market uncertainties force manufacturing companies to be flexible and responsive in producing different parts, by adapting the existing system without the need for a substantial investment. The market is characterized by time variations in product quantities and varieties while manufacturing systems remain inherently fixed. To sustain competitive manufacturing, a company has to adopt to new production requirements and be responsive to market changes quickly. Conscious decisions have to be made for a system to respond to market fluctuations. In order to respond to the dynamic changes, there is a need for developing methodologies that analyse, evaluate and control performance of manufacturing system at the system and/or process levels.

The primary focus of the thesis is to develop a novel generic framework for modelling and controlling manufacturing systems intending for improvement of the performance of manufacturing and make companies more competitive. The framework incorporates the complex interrelations between the process and system parameters, i.e., the dynamics of the system. Thus, provides a quantitative and qualitative analysis for performance evaluation and for optimizing performance of manufacturing system. The generic framework can further be adapted for studying specific manufacturing systems in discrete manufacturing. Three case studies are presented. The case studies are performed in an automotive company where the effect of various levels of control is investigated in manufacturing systems configured as transfer line or as a flexible manufacturing system.

Two aspects of the dynamic nature of manufacturing system are investigated in this thesis: (1) The engineering nature of the system, i.e., the selection of appropriate process parameters to manufacture a product according to the design specification, and (2) The business nature of the system, i.e., the selection of system parameters with respect to the way the product is manufactured. At the process level, the parameters are controlled within the process capability limits to adapt to the changes of the system parameters in response to the market dynamics. At the system level, operational parameters are controlled to satisfy performance criteria.

A case study for resource use analysis during primary processes has also been investigated and presented. The critical operations and the operations that have the highest energy consumptions and the potential for energy savings have been identified.

The methodology developed for analysing the performance of the dynamic manufacturing system is based on a system dynamics modelling approach. Results obtained from different modelling approaches are presented and compared based on the selected performance metrics.

Place, publisher, year, edition, pages
Stockholm: Kungliga Tekniska högskolan, 2018. p. 107
Series
TRITA-ITM-AVL ; 2018:33
Keywords
Manufacturing system and strategy; performance evaluation; manufacturing dynamics; decision-making; system dynamics; sustainable and energy efficient manufacturing
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production Engineering
Identifiers
urn:nbn:se:kth:diva-229400 (URN)978-91-7729-841-0 (ISBN)
Public defence
2018-06-15, M311, Brinellvägen 68, Stockholm, 13:00 (English)
Opponent
Supervisors
Funder
VINNOVA, 2012-00933
Available from: 2018-06-04 Created: 2018-06-01 Last updated: 2018-06-04Bibliographically approved

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Adane, Tigist FeteneArchenti, AndreasNicolescu, Mihai

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