4D BIM for Improving Plant Turnaround Maintenance Planning and Execution: A Case Study

2018 ◽  
Author(s):  
Wenchi Shou ◽  
Jun Wang ◽  
Xiangyu Wang
Keyword(s):  
Maintenance Planning

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.

Scheduling Maintenance Technicians in a Railway Depot

2021 ◽  
Author(s):  
Tiago Alves ◽  
António R. Andrade
Keyword(s):  
Programming Model ◽  
Crew Scheduling ◽  
Mixed Integer ◽  
Rolling Stock ◽  
Maintenance Planning ◽  
Labor Costs ◽  
Planning And Scheduling ◽  
Scheduling Model ◽  
Maintenance Technicians

Abstract This paper presents a mathematical programming model that optimizes the daily schedule of maintenance technicians in a railway depot. The aim of the model is the minimization of the associated labor costs, while assigning the different technicians and skills required for each maintenance task. A case study of a Portuguese train operating company is explored, including many technical constraints imposed by the company. A mixed-integer linear programming model is formulated and applied to the case study, while observing the rolling stock schedule and the maintenance tactical plan. The optimized solution shows that the maintenance team could be shortened, as some workers are not necessary to carry out all maintenance actions, suggesting the need for more flexible maintenance crew scheduling and associated labor conditions. The present model is integrated within a tactical maintenance planning model, which finds a feasible annual maintenance plan for the entire fleet, and an operational maintenance scheduling model, which assigns train units to service tasks and schedules the maintenance tasks within the rolling stock. Together, the three models provide a decision framework that can support maintenance planning and scheduling decisions. Finally, the present maintenance crew scheduling model adds a key aspect to the literature: the skills of maintenance technicians.

USCGC Healy (WAGB 20)—A Case Study for Implementing Reliability-Centered Maintenance

2000 ◽  
Vol 37 (01) ◽  
pp. 50-56
Author(s):  
William J. Reicks ◽  
Richard Burt ◽  
John P. Mazurana ◽  
Russell J. Steinle
Keyword(s):  
Planning Process ◽  
Technical Information ◽  
Cost Effective ◽  
Lessons Learned ◽  
Coast Guard ◽  
Fine Tuning ◽  
Maintenance Planning ◽  
Detail Design ◽  
Reliability Centered Maintenance

In new ship construction, maintenance planning affords both an opportunity and a challenge. On one hand, a new ship class enables maintenance planners to start with a clean slate and consider improved and more cost-effective maintenance methods. On the other hand, new manning concepts, lack of timely technical information when maintenance planning is conducted in parallel with detail design, use of equipment new to the fleet, and the like impose a measure of uncertainty on the planning process. In this paper, we review why and how Reliability-Centered Maintenance (RCM) techniques were applied to the new Polar icebreaker U.S. Coast Guard Cutter (CGC) Healy (frontispiece). We review how we incorporated condition-based maintenance techniques where appropriate. We discuss the decision process used for fine-tuning the Maintenance Procedure Cards (MPC) for CGC Healy's hull, mechanical, and electrical (HM&E) Preventive Maintenance Manual. Finally, we share some lessons learned in the process.

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