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

Abstract

PurposeSeeks 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/approachIn 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.FindingsA 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/valueIt could be assumed that machines in future manufacturing systems will provide automatic data. The data can then be used for DES models when identifying bottle‐necks in a manufacturing system.

Simulation analysis for managing and improving productivity

“…The methodology that is followed in this paper to perform the simulation is illustrated in Figure 2. This methodology is common for most simulation work conducted (Ingemansson et al, 2005;Sandhu et al, 2013). Law (2007) explained that the methodology for simulation is not "strictly a sequential process."…”

“…The study was able to achieve 18 percent efficiency improvement and reduce scrap by 4 percent. Other scholarly work (Ingemansson et al, 2005;Greasley, 2005;Gunasekaran et al, 2000;Sandhu et al, 2013;Santos et al, 2012) using different software's such as QUEST, Arena, and Pro Model at different manufacturing facilities clearly illustrate the ability of simulation to identify problems and analyze alternatives achieving significant improvements. Generally, simulation studies vary based on the facility studied, product produced and proposals or scenarios considered.…”

“…The discrete-event simulation is capable of addressing a number of issues, such as (El-Khalil, 2009;Hlupic and de Vreede, 2005;Ingemansson et al, 2005;Law, 2007;Sandhu et al, 2013;and Santos et al, 2012):…”

An Open Source Tool for Automated Input Data in Simulation

“…The case study presented should be considered as proof of the KE tool for the automation of input data for DES. Research studies that also contribute in this area are presented by [25] and [26]. One of the main differences of the KE tool presented in this paper and these two studies is that the tool presented here provides "Data processing", in which the raw data is altered to map onto simulation input data, for example through distribution fitting.…”

A simulation-based methodology to analyse production line disruptions

“…Further, interaction of humans with processes and technology over time results in a large number of scenarios and outcomes which are difficult to comprehend and evaluate manually. Therefore, several authors (for example, Law and Kelton 2000, Ingemansson 2004, Ingemansson et al 2005, Hassan and Gruber 2008, Padhi and Mohapatra 2009, Garza-Reyes et al 2010, Huang et al 2011) have used a more systematic process simulation approach to identify and eliminate in-built disturbances in manufacturing systems and increase productivity. Process simulation helps decision makers to predict, compare, and optimise the performance of processes without the cost and risk of disrupting operations or building a sequence of new processes in a real setting.…”