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KPI Study for Mining Industry: Eliminate the Communication Gaps Within Organizations

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Original date: 
Friday, April 29, 2022
Abstract: 

Within the mining industry, the library of KPIs has not kept up with data that has become increasingly available through digitization, therefore leading to an overuse of lagging performance indicators. Additionally, due to the fact that strategic corporate goals are oftentimes built on the basis of soft or perceptual measures from stakeholders, which are subjective in nature, organizations struggle with the process of linking strategic level goals to KPIs on the shop floor. Therefore, creating a communication gap between technical teams and senior management. As a consequence, maintenance leaders have a difficult time demonstrating the added value that maintenance activities create with an organization, leading to challenges in securing the resources required for things such as continuous improvement projects. Considering that the implementation of a robust KPI framework is an alignment of three key areas: people, process, and technology, the first portion of this presentation will be investigating a holistic approach to developing maintenance KPIs that are integrated into corporate strategic goals. Therefore, outlining the steps required for organizational leaders to begin standardizing data gathering procedures and creating a trustworthy system that can be leveraged for decision making. Aside from the previously discussed administrative challenges associated with data gathering within organizations, it must also be highlighted that KPIs are collected on a monthly or quarterly basis, meaning that training sets for forecasting models are extremely limited. Therefore, in order to address the reliance on lagging performance indicators within maintenance departments, a variety of time series models capable of achieving high accuracy on small datasets will be discussed along with direct business applications. Through achieving these goals, the intended outcome is to create a more contemporary data driven methodology for selecting organizational KPIs, as well as directly demonstrating the added value that the various business units create within the organization.

BoK Content Source: 
MainTrain 2022
BoK Content Type: 
Presentation Slides
Video
Asset Management Framework Subject: 
01 Strategy & Planning, 1.02 Asset Mgmt Strategy & Objectives, 2.00 Asset Management Decision Making General, 2.02 Operations & Maintenance Decision-Making, 03 Lifecycle Delivery, 3.05 Maintenance Delivery, 05 Organization & People, 5.02 Asset Management Leadership
Maintenance Management Framework Subject: 
01 Business & Organization Context, 1.1 Requirements & Expectations, 02 Maintenance Program Mgmt, 2.1 Maintenance Requirements, 09 Information Management, 9.2 Standards & Specification, 10 Continuous Improvement, 10.1 Metrics / KPIs, 10.3 Maintenance Management Improvements, 10.4 Maintenance Practices Improvements
Author Title: 
MEng Student
Author Employer: 
University of Toronto
Author Bio: 

Gabriel Merisanu is a dedicated and driven Chemical Engineer from the University of Toronto that is currently pursuing a Master of Engineering within the department of Mechanical and Industrial Engineering with an emphasis in analytics and management. With 2 years of professional experience in consulting and project management, Gabriel is passionate about leveraging this past industry knowledge while exploring greater meaning within his career and the positive impact engineering can have on society. As of September 2022, Gabriel will be joining the Guidehouse Energy, Sustainability, and Infrastructure team as a consultant.

Author 2 Title: 
Master of Engineering Student
Author 2 Bio: 
Blair is a first year M.Eng student in Mechanical and Industrial Engineering program with emphasis in data analytics and healthcare engineering. She is currently working on development of KPI (Key Performance Indicator) for mining sector project. Her work is focused on evaluating the factors affecting the maintenance effectiveness and verify the indicators’ appropriateness for mining industries.