Torbjörn Ylipää

Reducing bottle-necks in a manufacturing system with automatic data collection and discrete-event simulation

Purpose – Seeks to present a methodology for working with bottle‐neck reduction by using a combination of automatic data collection and discrete‐event simulation (DES) for a manufacturing system.Design/methodology/approach – In the DES model, the bottle‐neck was identified by studying the simulation runs based on the collected automatic data from the different machines in the manufacturing system.Findings – A case study showed an improvement of the availability in one machine from 58.5 to 60.2 percent. This single alteration with a minimum of investment resulted in a 3 percent increase of the overall output in the manufacturing system consisting of 11 numerically controlled machines and six other stations. A new simulation run was performed one year after the first study in order to see how the improvement work has progressed with the suggested method. The method resulted in an increase of 6 percent in overall output.Originality/value – It could be assumed that machines in future manufacturing systems wil...

Identification of maintenance improvement potential using OEE assessment

Purpose – The purpose of this paper is to identify maintenance improvement potentials using an overall equipment effectiveness (OEE) assessment within the manufacturing industry. Design/methodology/approach – The paper assesses empirical OEE data gathered from 98 Swedish companies between 2006 and 2012. Further analysis using Monte-Carlo simulations were performed in order to study how each OEE component impacts the overall OEE. Findings – The paper quantifies the various equipment losses in OEE, as well as the factors availability, utilization, speed, quality, and planned stop time. From the empirical findings, operational efficiency losses are found to have the largest impact on OEE followed by availability losses. Based on the results, improvement potentials and future trends for maintenance are identified, including a systems view and an extended scope of maintenance. Originality/value – The paper provides detailed insights about the state of equipment effectiveness in terms of OEE in the manufacturing industry. Further, the results show how individual OEE components impact overall productivity and efficiency of the production system. This paper contributes with the identification of improvement potentials that are necessary for both practitioners and academics to understand the new direction in which maintenance needs to move. The authors argue for a service-oriented organization. Keywords Manufacturing, Overall equipment effectiveness, Maintenance,Production service and maintenance systems Paper type Research paper

Handling of Production Disturbances in the Manufacturing Industry

Purpose – A common understanding of what events to regard as production disturbances (PD) are essential for effective handling of PDs. Therefore, the purpose of this paper is to answer the two questions: how are individuals with production or maintenance management positions in industry classifying different PD factors? Which factors are being measured and registered as PDs in the companies monitoring systems? Design/methodology/approach – A longitudinal approach using a repeated cross-sectional survey design was adopted. Empirical data were collected from 80 companies in 2001 using a paper-based questionnaire, and from 71 companies in 2014 using a web-based questionnaire. Findings – A diverging view of 21 proposed PD factors is found between respondents in manufacturing industry, and there is also a lack of correspondence with existing literature. In particular, planned events are not classified and registered to the same extent as downtime losses. Moreover, the respondents are often prone to classify factors as PDs compared to what is actually registered. This diverging view has been consistent for over a decade, and hinders companies to develop systematic and effective strategies for handling of PDs. Originality/value – There has been no in-depth investigation, especially not from a longitudinal perspective, of the personal interpretation of PDs from people who play a central role in achieving high reliability of production systems.