Simulation as an enabler for organizational excellence

O'Kane, James

doi:10.1108/13683040310509278

Cited by 14 publications

(11 citation statements)

References 14 publications

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“…Potentially, companies ranging from small to large can benefit significantly through the appropriate utilisation of DES. However, while there is a vast and evolving literature on applied DES studies, the majority of studies conducted tend to be within a larger firm context (Aqlan et al, 2014;Azadeh et al, 2011;Bengtsson et al, 2009;Byrne et al, 2010;Fowler and Rose, 2004;Liston et al, 2007;Mayer and Spieckermann, 2010;Nidumolu et al, 1998;O'Kane et al, 2007;Sharda and Bury, 2012 Aids in superior manufacturing facility design with less-costly mistakes Sources: Ahmed and Latif (2010), Banks (1999), Fowler and Rose (2004), Liotta (2012) and O'Kane (2003) Table I. Selection of potential benefits of DES to companies 164 JSBED 23,1 themselves to effectively adopting DES, such as the necessary level of organisational complexity, the required level and format of data needed for DES and the necessary budget to support DES.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…While the emphasis in research and implementation of DES studies in the past has mostly been focused on such large organisations, there are some reported cases where DES has been applied to SMEs (Ahmed and Latif, 2010;Byrne and Heavey, 2004;Geraghty and Heavey, 1999;Hvolby et al, 2012;Jain and Leong, 2005;Jarkko et al, 2013;Liotta, 2012;Mahfouz et al, 2011;Mosca et al, 2005;Nisula and Pekkola, 2012;O'Kane, 2003;Swarnkar and Harding, 2009). Studies of SME simulation have been sporadic and mostly explored on a one off, case-by-case basis (Hvolby et al, 2012;Jarkko et al, 2013;Mahfouz et al, 2011) which is in line with reported expectation, as investigating simulation within the SME context presents a number of additional challenges (Liotta, 2012;O'Kane, 2003). Examples of such additional challenges relate to the complex process of simulation in comparison to the scale of the organisation, availability and format of data for simulation modelling, time and resources required to execute the model, lack of awareness, cost and experience factors and the under-estimation of the advantages that can be gained through the use of DES tools (Law and Kelton, 1991;Liotta, 2012;O'Kane et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

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Analysis of SME data readiness: a simulation perspective

Ivers

Byrne

2016

Journal of Small Business and Enterprise Development

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Purpose – The purpose of this paper is to investigate the data profile of manufacturing small and medium enterprises (SMEs) with specific emphasis on understanding the data readiness of SMEs for discrete event simulation (DES) modelling. Design/methodology/approach – Research was conducted through a review of literature and a survey research strategy of manufacturing SMEs. Findings – This paper illustrates the data profile of manufacturing SMEs. Insight is provided on the types of data collected by SMEs, the collection methods used and how these data are stored by the SMEs. Additionally size and age effects are considered. Based on this data profile, conclusions are made regarding an indication of data readiness of manufacturing SMEs for DES modelling. Research limitations/implications – This research is focused specifically on manufacturing SMEs in Ireland, other countries and sectors are not investigated. Practical implications – This paper provides owner-managers and senior management insight into the data profile of manufacturing SMEs and their potential for utilisation of DES for performance improvement and decision support. Originality/value – This paper addresses the gaps that exist in the knowledge of the data profile of manufacturing SMEs and consequently the status of this profile with regard to the readiness of SMEs for DES modelling.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of SME data readiness: a simulation perspective

Ivers

Byrne

2016

Journal of Small Business and Enterprise Development

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“…Computer-based simulation can take many forms, but generally the technique is applied by developing a computer model using either a simulation language, package, tool or integrated environment system (O'Kane, 2003). Discrete-event simulation is "the modelling of a system as it evolves over time, by a representation in which the state variables change instantaneously at separate points in time" (Law and Kelton, 1991).…”

Section: Lean Park Homes Productionmentioning

confidence: 99%

The development of a lean park homes production process using process flow and simulation methods

Garza-Reyes

Oraifige

Soriano‐Meier

et al. 2012

Journal of Manufacturing Technology Management

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Purpose -Continuous process flow is a prerequisite of lean systems as it helps to reduce throughput times, improve quality, minimize operational costs, and shorten delivery times. The purpose of this paper is to empirically demonstrate the application of a methodology that combines a time-based study, discrete-event simulation and the trial and error method to enable a leaner process through more efficient line balancing and more effective flow for a park homes production process. This method is replicable across other contexts and industry settings. Design/methodology/approach -The paper reviews the UK park homes production industry and, specifically, a major factory that builds these homes. It compares the factory method to traditional on-site construction methods. An empirical study of production times was carried out to collect data in order to analyse the current workload distribution and the process flow performance of the park homes production process. Finally, seven discrete-event simulation models were developed in order to test different scenarios and define the optimum line balance for every section of the production process. Findings -By combining time study, discrete-event simulation and trial and error methods, the workload distribution and process flow performance of the park homes production line were analysed and improved. A reduction of between 1.82 and 36.32 percent in balancing losses in some sections of the process was achieved. Practical implications -This paper supports current knowledge on process flow improvement and line balancing by exploring and analysing these issues in a real-life context. It can be used to guide production management practitioners in their selection of methods and demonstrates how they are exploited when seeking to improve process flow, efficiency and line balancing of production operations. Originality/value -The study uses a real industrial application to demonstrate how the methodological combination and deployment of process flow improvement strategies, such as time study, simulation, and trial and error, can help organisations achieve process flow improvements and, as a consequence, a leaner production process.

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“…Continuous assessment on the functionality and operability of the project product and feedback mechanism allow dynamic interaction and evaluation of the project's performance over the life cycle of projects (O'Kane, 2003).…”

Section: Framework For Simulation Analysismentioning

confidence: 99%

Adding Value in Construction Design Management by Using Simulation Approach

Doloi¹

2008

Robotics and Automation in Construction

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Simulation as an enabler for organizational excellence

Cited by 14 publications

References 14 publications

Analysis of SME data readiness: a simulation perspective

Analysis of SME data readiness: a simulation perspective

The development of a lean park homes production process using process flow and simulation methods

Adding Value in Construction Design Management by Using Simulation Approach

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