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A review of function blocks for process planning and control of manufacturing equipment
University of Skovde.ORCID iD: 0000-0001-8679-8049
University of Skovde.
University of Skovde.
De Montfort University.
2012 (English)In: Journal of manufacturing systems, ISSN 0278-6125, Vol. 31, no 3, 269-279 p.Article in journal (Refereed) Published
Abstract [en]

Manufacturing in a job-shop environment is often characterized by a large variety of products in small batch sizes, requiring real-time monitoring for dynamic distributed decision making, and adaptive control capabilities that are able to handle, in a responsive way, different kinds of uncertainty, such as changes in demand and variations in production capability and functionality. In many manufacturing systems, traditional methods. based on offline processing performed in advance, are used. These methods are not up to the standard of handling uncertainty, in the dynamically changing environment of these manufacturing systems. Using real-time manufacturing intelligence and information to perform at a maximum level, with a minimum of unscheduled downtime, would be a more effective approach to handling the negative performance impacts of uncertainty. The objective of our research is to develop methodologies for distributed, adaptive and dynamic process planning as well as machine monitoring and control for machining and assembly operations, using event-driven function blocks. The implementation of this technology is expected to increase productivity, as well as flexibility and responsiveness in a job-shop environment. This paper, in particular, presents the current status in this field and a comprehensive overview of our research work on function block-enabled process planning and execution control of manufacturing equipment

Place, publisher, year, edition, pages
2012. Vol. 31, no 3, 269-279 p.
Keyword [en]
Adaptability, Process planning, Function block, CNC machining, Assembly
National Category
Production Engineering, Human Work Science and Ergonomics
URN: urn:nbn:se:kth:diva-122554DOI: 10.1016/j.jmsy.2012.02.004ISI: 000309574900001OAI: diva2:622761
XPRES - Initiative for excellence in production research

QC 20130528

Available from: 2013-05-23 Created: 2013-05-23 Last updated: 2013-05-28Bibliographically approved

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Wang, Lihui
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