scholarly journals Winning Asset Management Improvement Team: Maintenance Planning and Scheduling in a Highly Regulated Environment

2021 ◽  
Author(s):  
Eric Patterson ◽  
Zach Yost
Keyword(s):  
Asset Management ◽  
Maintenance Planning ◽  
Planning And Scheduling ◽  
Improvement Team ◽  
Management Improvement

scholarly journals A Taxonomy of Railway Track Maintenance Planning and Scheduling: A Review and Research Trends

2021 ◽  
pp. 107827
Author(s):  
Mahdieh Sedghi ◽  
Osmo Kauppila ◽  
Bjarne Bergquist ◽  
Erik Vanhatalo ◽  
Murat Kulahci
Keyword(s):  
Research Trends ◽  
Railway Track ◽  
Maintenance Planning ◽  
Planning And Scheduling ◽  
Track Maintenance

Integration of a Maintenance Management Model (MMM) Into an Asset Management Process

2022 ◽  
pp. 1-29
Author(s):  
Carlos A. Parra ◽  
Adolfo Crespo Márquez ◽  
Vicente González-Prida ◽  
Antonio Sola Rosique ◽  
Juan F. Gómez ◽  
...  
Keyword(s):  
Life Cycle ◽  
Continuous Improvement ◽  
Asset Management ◽  
Maintenance Management ◽  
Management Model ◽  
Management Process ◽  
Planning And Scheduling ◽  
The Cost ◽  
And Control ◽  
The Relationship

The chapter explains in detail the maintenance management model (MMM) taken as a reference for the development of the book. The chapter is based on the eight phases of the MMM. The first three blocks determine the effectiveness of the management; the following blocks assure the same efficiency and continuous improvement in the following way: Blocks 4 and 5 include actions for the planning and scheduling of maintenance, including, of course, the capacity of planning of department of maintenance. Blocks 6 and 7 are dedicated to the evaluation and control of the maintenance and the cost of assets throughout their life cycle. This chapter of introduction briefly summarizes the process and the reference frame necessary for the implementation of the MMM. This chapter also presents the relationship between the eight phases of the maintenance management model proposed and the general requirements of the asset management standard ISO 55000 to show how the gradual implementation of the MMM largely covers the requirements of the standard ISO 55000.

scholarly journals Indicators for maintenance planning based on energy efficiency in heat exchanger networks

2020 ◽  
Vol 25 (3) ◽  
pp. 367-371
Author(s):  
Daniel Enrique Yabrudy-Mercado ◽  
Bienvenido Sarria Sarria López-Sarria ◽  
Juan G. Fajardo-Cuadro ◽  
Camilo A. Cardona-Agudelo
Keyword(s):  
Energy Efficiency ◽  
Heat Exchanger ◽  
Asset Management ◽  
Energy Use ◽  
Initial Conditions ◽  
Maintenance Planning ◽  
Maintenance Schedule ◽  
Heat Exchanger Networks ◽  
The Status ◽  
Productive Asset

Thanks to the asset management regulations, modern maintenance practices are rapidly getting a more managerial role, and is used to achieve savings and optimize energy use. Therefore, knowing at all times the status of the equipment allows for timely and necessary interventions that generate value to the company, and recover the initial conditions of them. Heat exchanger networks, rather than a productive asset, constitute an energy-saving strategy, to have lower fuel costs, emission control, rational use of energy, etc. in the atmospheric furnaces of the crude distillation units, and other units that perform similar processes. Thus, keeping them in their best conditions, most of the time is necessary. In this paper, we propose a methodology for the diagnosis of the equipment of the network, and the maintenance planning justified by the energy efficiency of them and the economic impact of the intervention. In addition, an indicator is presented to provide an economic justification for maintenance interventions, as well as for briefly showing the results of the application of maintenance mainly on efficiency and the use of the KPI J proposed for programming the maintenance schedule of some of the equipment (pilot test) of the heat exchanger network under study. The methodology developed uses real operation values, and its results provided savings up to USD 150,000.

scholarly journals Predicting maintenance work hours in maintenance planning

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Waqas Khalid ◽  
Simon Holst Albrechtsen ◽  
Kristoffer Vandrup Sigsgaard ◽  
Niels Henrik Mortensen ◽  
Kasper Barslund Hansen ◽  
...  
Keyword(s):  
Industrial Applications ◽  
Research Literature ◽  
Work Hours ◽  
Machine Learning Algorithms ◽  
Maintenance Planning ◽  
Planning And Scheduling ◽  
Content Type ◽  
Work Hour ◽  
Maintenance Work

PurposeCurrent industry practices illustrate there is no standard method to estimate the number of hours worked on maintenance activities; instead, industry experts use experience to guess maintenance work hours. There is also a gap in the research literature on maintenance work hour estimation. This paper investigates the use of machine-learning algorithms to predict maintenance work hours and proposes a method that utilizes historical preventive maintenance order data to predict maintenance work hours.Design/methodology/approachThe paper uses the design research methodology utilizing a case study to validate the proposed method.FindingsThe case study analysis confirms that the proposed method is applicable and has the potential to significantly improve work hour prediction accuracy, especially for medium- and long-term work orders. Moreover, the study finds that this method is more accurate and more efficient than conducting estimations based on experience.Practical implicationsThe study has major implications for industrial applications. Maintenance-intensive industries such as oil and gas and chemical industries spend a huge portion of their operational expenditures (OPEX) on maintenance. This research will enable them to accurately predict work hour requirements that will help them to avoid unwanted downtime and costs and improve production planning and scheduling.Originality/valueThe proposed method provides new insights into maintenance theory and possesses a huge potential to improve the current maintenance planning practices in the industry.

Models for maintenance planning and scheduling – a citation-based literature review and content analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Syed Asif Raza ◽  
Abdul Hameed
Keyword(s):  
Content Analysis ◽  
Literature Review ◽  
Citation Analysis ◽  
Citation Network ◽  
Maintenance Planning ◽  
Bibliometric Data ◽  
Planning And Scheduling ◽  
Content Type ◽  
Network Analyses ◽  
Research Studies

PurposeThe findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.Design/methodology/approachWe have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.FindingsBA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.Originality/valueThere are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.

Sign in / Sign up

Export Citation Format

Share Document