The pursuit of operational excellence in the manufacturing industry is at rise, but its measurement still lacks of appropriate indicators to determine its financial benefits. The ambiguity is due to the impact arisen from manufacturing fluctuations such as price and cost, production mix, and direct and indirect parameters variations. Manufacturing fluctuations distort the cost benefit of operational excellence. This paper therefore proposes the OEP (Operational Excellence Profitability) indicators to isolate the impact of manufacturing fluctuation, and distinctly identify the payback of operational excellence strategies and initiatives through cost benefits of achieving higher efficiency and yield. The paper presents the conceptual and mathematical development of the proposed OEP indicators and the formulas used for their calculation. Hypothetical and industrialbased investigations and applications of the OEP indicators are conducted for their validation. The results obtained from the hypothetical exercise and industrial case suggest that OEP indicators can provide an effective cost benefit analysis of operational excellence. This would contribute in providing manufacturing organisations with more complete information regarding the performance of their processes, which will allow their directors and managers to take better decisions related to the management and improvement of their processes.
PurposeEquipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.Design/methodology/approachThe research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.FindingsThe findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.Practical implicationsManufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.Originality/valueThe study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.