| 1. |
- Bokrantz, Jon, 1988, et al.
(author)
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A Methodology for Continuous Quality Assurance of Production Data
- 2016
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In: Proceedings - Winter Simulation Conference. - 0891-7736. ; 2016-February, s. 2088-2099
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Conference paper (peer-reviewed)abstract
- High quality input data is a necessity for successful Discrete Event Simulation (DES) applications, and there are available methodologies for data collection in DES projects. However, in contrast to standalone projects, using DES as a day-to-day engineering tool requires high quality production data to be constantly available. Unfortunately, there are no detailed guidelines that describes how to achieve this. Therefore, this paper presents such a methodology, based on three concurrent engineering projects within the automotive industry. The methodology explains the necessary roles, responsibilities, meetings, and documents to achieve a continuous quality assurance of production data. It also specifies an approach to input data management for DES using the Generic Data Management Tool (GDM-Tool). The expected effects are increased availability of high quality production data and reduced lead time of input data management, especially valuable in manufacturing companies having advanced automated data collection methods and using DES on a daily basis.
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| 2. |
- Barletta, Ilaria Giovanna, 1988, et al.
(author)
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Assessing a proposal for an energy-based overall equipment effectiveness indicator through discrete event simulation
- 2015
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In: Proceedings - Winter Simulation Conference. - 0891-7736. - 9781479974863 ; 2015-January, s. 1096-1107
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Conference paper (peer-reviewed)abstract
- New challenges demand that manufacturing companies adopt sustainable approaches and succeed in this adoption. Energy efficiency plays a key role in achieving sustainability goals, and performance indicators are necessary beyond measurement of data to evaluate energy efficiency. In this landscape, scalable and easy-to-understand metrics providing an energy competitiveness degree of manufacturing resources are currently missing. The study aims to test through simulation applicability and potential offered by a novel Energy Overall Equipment Effectiveness - Energy OEE - indicator for discrete manufacturing firms. A simulation of a discrete manufacturing CNC machine case is used to evaluate the applicability of using Energy OEE assessment for management decision support. As a result, this study paves the way to a better exploitation of data that energy monitoring and sensor technology aim to offer in the future.
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| 3. |
- Johansson, Björn, 1975, et al.
(author)
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Power Level Sampling of Metal Cutting Machines for Data Representation in Discrete Event Simulation
- 2015
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In: International Journal of Production Research. - : Informa UK Limited. - 0020-7543 .- 1366-588X. ; 53:23, s. 7060-7070
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Journal article (peer-reviewed)abstract
- An extension to the application area for discrete event simulation (DES) has been ongoing since the last decade and focused only on economic aspects to include ecologic sustainability. With this new focus, additional input parameters, such as electrical power consumption of machines, are needed. This paper aim at investigating how NC machine power consumption should be represented in simulation models of factories. The study includes data-sets from three different factories. One factory producing truck engine blocks, one producing brake disc parts for cars and one producing forklift components. The total number of data points analysed are more than 2,45,000, where of over 1,11,000 on busy state for 11 NC machines. The low variability between busy cycles indicates that statistical representations are not adding significant variability. Furthermore, results show that non-value-added activities cause a substantial amount of the total energy consumption, which can be reduced by optimising the production flow using dynamic simulations such as DES.
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