Maintenance Productivity Measurement: Case Study of a Manufacturing Company

Alli, O.A.; Ogunwolu, Ladi; M.O, Oke

doi:10.4028/www.scientific.net/amr.62-64.565

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…According to (Alli, et al, 2009) the utility values for each of the performance measures were derived as follows:…”

Section: Example 1 (Analytical): Single Breakdown Queue and Single Mamentioning

confidence: 99%

“…From the case study by (Alli et al, 2009), they selected the following six performance measures mentioned in (Priel, 1974): Figure 1. System dynamics approach: defects accumulation measurement scheme that gives good management information in areas critical to increasing productivity as well as being amenable to easy data collection.…”

Section: The Composite Approachmentioning

confidence: 99%

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Modeling Maintenance Productivity Measurement

Bolu

Integrated Models for Information Communication Systems and Networks

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Modeling and simulation of industrial information communication systems and networks is one of the major concerns of productivity engineers for the establishment of productivity standards in virtually all functional areas of an industrial organization. Maintenance function is one of such areas that have always engaged the attention of engineering productivity practitioners. However, one of the basic problems is the difficulty in setting up integrated but easy and practical measurement schemes. Even where the measures are set up, the approaches to measurement sometimes are conflicting. Therefore the need for an integrated approach to optimize the basket of parameters measured remains. In this chapter the author attempts to identify approaches in integrated and systematic maintenance productivity measurement and create models for optimising total productivity in maintenance systems. Visual yardstick, utility, queuing systems and simulations approaches for measurement of maintenance productivity are all discussed with a particular focus on markov chain approach for stochastic breakdowns in repairable systems.. The chapter also shows how understanding the impact of plant failure and repair/service distributions assists in providing measures for maintenance productivity using discrete event system simulation.

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“…According to (Alli, et al, 2009) the utility values for each of the performance measures were derived as follows:…”

Section: Example 1 (Analytical): Single Breakdown Queue and Single Mamentioning

confidence: 99%

Section: The Composite Approachmentioning

confidence: 99%

Modeling Maintenance Productivity Measurement

Bolu

Integrated Models for Information Communication Systems and Networks

View full text Add to dashboard Cite

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An Assessment of the Determinants of Productivity in the Electricity Industry in Nigeria

Olatunji

2018

ESJ

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The study examined the productivity in the electricity industry in Nigeria. The aim of the study was to ascertain the determinants of productivity in the electricity sector. The research design adopted for the study was a longitudinal study of productivity in the electricity industry in Nigeria. The study considered time series data for a 20 year period from 1996 to 2015. Data on study variables were obtained from Central Bank of Nigeria (CBN) statistical bulletins, National Bureau of Statistics (NBS) annual publications, and the websites of both Transparency International (TI) and Energy Information Administration (EIA). Based on the study objectives, the fully modified ordinary least square (FM-OLS) technique was used to estimate the multiple regressions between productivity and the explanatory variables. Data analyses were carried out using the software application of E- View 9.0. Results from the study showed that the total factor productivity which is an indication of efficiency in the electricity sector was 0.29. This is low when compared with international best practice of 0.80. Also, results from the study revealed that funding, weather condition, vandalism and labour supply have significant effect on productivity of the electricity industry in Nigeria. However, tariff structure and corruption were not statistically significant in the prediction of productivity in the electricity industry. The study recommended that increased budgetary allocations should be made available to the electricity industry to provide the needed improvements in the sector.

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Maintenance Productivity Measurement: Case Study of a Manufacturing Company

Cited by 2 publications

References 3 publications

Modeling Maintenance Productivity Measurement

Modeling Maintenance Productivity Measurement

An Assessment of the Determinants of Productivity in the Electricity Industry in Nigeria

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