An analysis of managerial factors affecting the implementation and use of overall equipment effectiveness

Aminuddin, Nur Ainunnazli Binti; Garza‐Reyes, Jose Arturo; Kumar, Vikas; Antony, Jiju; Rocha-Lona, Luis

doi:10.1080/00207543.2015.1055849

Cited by 60 publications

(71 citation statements)

References 40 publications

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“…The errors of meeting the target (1 or 100%) were evaluated using Eqn. (2). Non-meeting the target (errors that are more than zero) required introduction of sigma metrics,  as improvement tool.…”

Section: Analysis Of Model Parametersmentioning

confidence: 99%

“…One of the best measures of efficiency is Overall Equipment Effectiveness (OEE) [1]. Overall Equipment Effectiveness (OEE) is a widely used performance indicator in manufacturing industries around the world [2]. It was initiated when Nakajima [3] introduced the Total Productive Maintenance (TPM) concept where the main goal is to improve and sustain equipment efficiency.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Smart Oee-Sigma Model for Production Process Optimization

Kareem¹,

Alabi²,

Ogedengbe³

et al. 2019

J. Prod. Eng.

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The quest for effective utilization of both humans and machinery is on the increase in order to survive competition. Overall Equipment Effectiveness (OEE) metric application in industry has been facing a challenge of continuing advancement in industrial operations. A smart OEE is required for a quick response to the dynamism in industrial system. In this study, OEE metric is made smart by integrating sigma continuous improvement tool into it for the enhancement of dynamism required of the traditional OEE model measured basically on three factorsavailability, performance and quality. System productivity dynamism is measured and predicted through sigma statistical variation of the production process defined as a ratio of delivered output (supply) to the expected (planned) output. The model was applied to a production process of fast moving product. The results obtained for the seven consecutive years (2006 to 2013) for traditional OEE are 100%, 92%, 84%, 86%, 89%, 81%, and 84%, respectively. In the new OEE-Sigma method, productivity can be continuously improved over the years by at most 77%. This indicated that smart OEE-sigma model is a better tool for enhancing continuous improvement in a dynamical processing environment.Pametan OEE-sigma model za optimizaciju procesa proizvodnje. Potraga za efikasnom upotrebom kako ljudi tako i mašina je u porastu kako bi preživeli konkurenciju. Primena metričkih efekata na ukupnu efikasnost opreme (OEE) u industriji je pred izazovom stalnog napretka industrijskih operacija. Pametni OEE je potreban za brz odgovor na dinamiku u industrijskom sistemu. U ovoj studiji, OEE metrika je napravljena pametnom integracijom sigma kontinuinualnog alata za poboljšanje njega kao i poboljšanje dinamičnosti koja se zahteva od tradicionalnog OEE modela koji se meri u osnovi na tri faktora -dostupnost, performanse i kvalitet. Dinamika produktivnosti sistema se meri i predviđa sigma statističkom varijacijom proizvodnog procesa definisanog kao odnos isporučene proizvodnje (ponude) i očekivanog (planiranog) izlaza. Model je primenjen u procesu proizvodnje proizvoda koji se brzo kreće. Dobijeni rezultati za sedam uzastopnih godina (od 2006. do 2013. godine) za tradicionalne OEE su 100%, 92%, 84%, 86%, 89%, 81% i 84%, respektivno. U novoj OEE-Sigma metodi, produktivnost se može kontinuirano poboljšavati tokom godina za najviše 77%. Ovo je pokazalo da je pametni OEE-sigma model bolji alat za poboljšanje kontinualnog poboljšanja u dinamičkom okruženju za obradu. Ključne reči: Smart OEE, Sigma metrika, kontinualno poboljšanje, proizvodni proces AKNOWLEDGEMENT BAT company Nigeria is acknowledged for allowing the collection of necessary information used in this study.

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Section: Analysis Of Model Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Smart Oee-Sigma Model for Production Process Optimization

Kareem¹,

Alabi²,

Ogedengbe³

et al. 2019

J. Prod. Eng.

View full text Add to dashboard Cite

show abstract

“…Although, the real potential of using these measures as improvement and decisions drivers is not fully used in industry today due, eg, to ambiguities in definitions and in their interpretation and to a lack of knowledge about the concept of lean production and their potential to create opportunities for developing efficient manufacturing systems. 20,21 In this line, a well-known concept of improving production performance is total productive maintenance (TPM), 22 a lean tool well known as an approach that integrates the maintenance and production with the organizational strategy to optimize equipment reliability and ensure efficiency management, encouraging employee involvement, eg, the autonomous maintenance by operators. 23 The immediate objective of TPM is the total elimination of production losses (zero failures, zero-quality defects, and zero losses of performance) converging to the overall asset effectiveness, reducing costs and increasing productivity.…”

Section: Introductionmentioning

confidence: 99%

Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

Viveros

Kristjanpoller

López-Campos

et al. 2018

Quality & Reliability Eng

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This article presents a graphical tool for the monitoring of performance indicators called GAOEM (Graphical Analysis for Overall Effectiveness Management). GAOEM comprehends the main indicators of maintenance and operations management, and it constitutes an adaptation of the overall effectiveness index. GAOEM facilitates control and analysis by using specific indicators in a graphic panel, designed for industries with high investment in physical assets. It also facilitates an efficient reading and interpreting of the data, enriching the analysis, the search for phenomena of interest and improvement opportunities to support the decision making. GAOEM requires 3 categories of input data, which are interventions data, time data, and production/process data. With this information, the basic performance indicators are calculated, being these indicators fundamental for the control and monitoring of the performance level. Later, these indicators will be the basis for calculation of both partial and total performance. GAOEM can be used as a diagnosis, analysis, control and monitoring tool for the indicators of interest at a strategic level, as well as a tool for searching of phenomena typical of a specific stage of the life cycle of assets and also of those conditions resulting from improper operation and/or maintenance, identifying their root causes.

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“…Therefore, the last two threats (i.e. observer error and observer bias) were not relevant in this case (Binti Aminuddin et al, 2016). …”

Section: Questionnaire Validity and Reliabilitymentioning

confidence: 99%

“…In this case, an electronic version of the questionnaire was developed using Qualtrics. This facilitated the respondents' access to the questionnaire via mobile devices and web browsers as well as the easy transfer of the collected data to an Excel spreadsheet for an easy export to IBM SPSS Statistics software version 2015 for statistical analysis (Binti Aminuddin et al, 2016). The questionnaire was adapted from those of Garza-Reyes et al (2012) and Antony and Desai (2009).…”

Section: Survey Questionnairementioning

confidence: 99%

Total quality environmental management: adoption status in the Chinese manufacturing sector

Garza‐Reyes

Kumar

et al. 2018

TQM

Self Cite

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Methodology/design/approach -A survey-based exploratory study was conducted based on 119 Chinese manufacturing companies and the data obtained was analysed using a combination of descriptive and inferential statistics. Findings -The results revealed that in general, there is less awareness of TQEM in the Chinese manufacturing sector than other environmental and quality/operations improvement approaches such as green supply chain management, reverse logistics, ISO 9000, Six Sigma and lean six sigma. Thus, its degree of implementation is also lower than these approaches as well as ISO 14001. The results also indicate that although a company's size is not associated to the implementation of TQEM, it is mainly large organisations and those that have adopted TQM those which will be mainly aware and have implemented TQEM. The study also reveal the drivers, results and challenges of TQEM implementation. Originality/value -The paper extends the currently limited knowledge on TQEM, and its results are beneficial for managers who aim at effectively adopting TQEM to simultaneously improve the environmental, operational and financial performance of their organisations. The paper can also motivate organisations not currently embarked on the "green wagon" to contemplate the benefits that implementing TQEM, or any other environmental management approach, may bring to their operations and business.

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An analysis of managerial factors affecting the implementation and use of overall equipment effectiveness

Cited by 60 publications

References 40 publications

Smart Oee-Sigma Model for Production Process Optimization

Smart Oee-Sigma Model for Production Process Optimization

Graphical analysis for overall effectiveness management: A graphical method to support operation and maintenance performance assessment

Total quality environmental management: adoption status in the Chinese manufacturing sector

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