Increased Profit and Technical Condition Through New KPIs in Maintenance Management

Rødseth, Harald; Schjølberg, Per; Kirknes, Martin; Bernhardsen, Thor Inge

doi:10.1007/978-3-319-27064-7_49

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…It is anticipated that sustainability will benefit the O&G industry in the transition towards a sustainable economy [3]. Meanwhile, in their strategic focus on reducing costs and increasing productivity, the Asset Management ISO standards integrate maintenance with the concepts of production and logistics in order to gain a competitive advantage in a challenging environment [27]. Sustainable maintenance will boost entities' ability to achieve this objective by adopting performance indicators to measure the impacts of time losses and waste during production.…”

Section: Benefits Of Sustainable Maintenance For Offshore Platformsmentioning

confidence: 99%

Incorporating Sustainability and Maintenance for Performance Assessment of Offshore Oil and Gas Platforms: A Perspective

Olugu

Wong

et al. 2022

Sustainability

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The existence of external two-fold pressure regarding competitiveness and sustainable development in a capital-intensive industry supports the need for sustainable performance. However, endeavors to create a sustainable framework to measure the performance of the oil and gas (O&G) industry are mostly devoted to the production and supply chain of petrochemical products and rarely focus on a maintenance perspective. Motivated by such scarcity, the goal of this research was to discuss and articulate the performance assessment framework by integrating concepts of maintenance and sustainability in the O&G industry. This study proposed the use of a range of performance measures for assessing sustainability on offshore production and drilling platforms. The conceptual framework consists of four aspects of sustainability categorized into technical, environmental, social, and economic dimensions. Each measure was assigned according to its relevance at the strategic, tactical, and functional levels of maintenance decision making. The conceptual framework resulted in hierarchical clusters of twelve strategic indicators. These indicators consist of conventional measures as well as new ones relating to the safety and reliability on offshore platforms. The potential contribution of the present study is found in its intention to empower a better understanding of sustainable maintenance and encourage those making decisions about practical implementation within the O&G industry. This paper culminates with directions for future studies.

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Section: Benefits Of Sustainable Maintenance For Offshore Platformsmentioning

confidence: 99%

Incorporating Sustainability and Maintenance for Performance Assessment of Offshore Oil and Gas Platforms: A Perspective

Olugu

Wong

et al. 2022

Sustainability

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“…This cube represents all the variables that must be accounted for when calculating PLI. It has also been performed PLI calculation for the O&G industry [22] and also for qualitatively evaluation in the smelting industry and manufacturing industry [15].…”

Section: Pli In Manufacturingmentioning

confidence: 99%

Data-driven Predictive Maintenance for Green Manufacturing

Rødseth¹,

Schjølberg²

2016

Proceedings of the 6th International Workshop of Advanced Manufacturing and Automation

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Abstract-With the current situation of high demand of sustainable manufacturing, different stakeholders have clear expectations for more environmental manufacturing and at the same time minimizing the operational costs. The role of maintenance plays a key role in the path towards sustainable manufacturing. For achieving green manufacturing, more datadriven predictive maintenance strategies is needed and is expected to reduce energy consumption, maintenance resources in terms of spare parts, and reduction of consumables in terms of example lubrication. The overall bottom-line for the predictive maintenance strategy is increased availability, reduction of maintenance hours in terms of reactive maintenance activities, and increased profit for the manufacturing business. For a predictive maintenance strategy, it is crucial to develop Key Performance Indicators (KPIs) for the maintenance management. Today, common KPIs such as availability and different indicators for maintenance cost has been developed. When aiming for more green manufacturing, a more integrated application of maintenance KPIs are needed. Today, the KPI Profit Loss Indicator (PLI) has been developed and demonstrated in the saw mill industry and is regarded to support a more integrated approach in terms of Integrated Planning (IPL). The aim of this article is develop a structured approach for data-driven predictive maintenance aligned with the concept of PLI. Through a case study, the approach is partly demonstrated for the manufacturing industry. The results in this demonstration shows that the data-driven maintenance strategy will have a positive impact of the PLI value and provide a sustainable manufacturing in long-term.

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“…This indicator evaluates the different types of losses in production from an economic point of view. Also, PLI has been tested in different industry branches such as the petroleum industry [4] and manufacturing industry [5].…”

Section: Introductionmentioning

confidence: 99%

Smart Maintenance in Asset Management – Application with Deep Learning

Rødseth

Eleftheriadis

et al. 2020

Lecture Notes in Electrical Engineering

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With the onset the digitalization and Industry 4.0, the maintenance function and asset management in a company is forming towards Smart Maintenance. An essential application in smart maintenance is to improve the maintenance planning function with better criticality assessment. With the aid from artificial intelligence it is considered that maintenance planning will provide better and faster decision making in maintenance management. The aim of this article is to develop smart maintenance planning based on principles both from asset management and machine learning. The result demonstrates a use case of criticality assessment for maintenance planning and comprise computation of anomaly degree (AD) as well as calculation of profit loss indicator (PLI). The risk matrix in the criticality assessment is then constructed by both AD and PLI and will then aid the maintenance planner in better and faster decision making. It is concluded that more industrial use cases should be conducted representing different industry branches.

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Increased Profit and Technical Condition Through New KPIs in Maintenance Management

Cited by 7 publications

References 8 publications

Incorporating Sustainability and Maintenance for Performance Assessment of Offshore Oil and Gas Platforms: A Perspective

Incorporating Sustainability and Maintenance for Performance Assessment of Offshore Oil and Gas Platforms: A Perspective

Data-driven Predictive Maintenance for Green Manufacturing

Smart Maintenance in Asset Management – Application with Deep Learning

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