Proceedings of the ASME 2018 International Manufacturing Science and Engineering Conference, MSEC 2018 MSEC 2018 June 18-22, 2018, College Station, USA MSEC2018-6492 DEVELOPING MAINTENANCE KEY PERFORMANCE INDICATORS FROM MAINTENANCE WORK ORDER DATA Michael P. Brundage ∗ KC Morris National Institute of Standards and Technology Gaithersburg, MD, USA Thurston Sexton Sascha Moccozet Michael Hoffman National Institute of Standards and Technology Gaithersburg, MD, USA ABSTRACT Maintenance management for manufacturing is a crucial activity for improving productivity within a facility. Within this process, maintenance work orders (MWOs) are used when track- ing and solving any maintenance–related issue. The MWOs often capture the problem, the solution, at what machine the problem occurred, who solved the problem, when the problem occurred, and other information. These MWOs are manually written by maintenance technicians, entered into a database, or recorded directly into maintenance management software. Technicians of- ten describe or record information informally — or do not record it at all — leading to inconsistencies and/or inaccuracies in the data. This paper outlines maintenance key performance indica- tors (KPIs), developed using MWOs, that show why consistent and accurate data collection is important for maintenance de- cision making. The maintenance data, or “elements,” and their corresponding KPIs are derived from MWOs from real manufac- turers (large manufacturers and small and medium enterprises). While all elements or KPIs are not recorded by every manufac- turer, the guideline provided here outlines the elements necessary to calculate specific KPIs. These examples are developed to aid in common maintenance decisions. INTRODUCTION As manufacturers face increasing global competition, meth- ods to increase productivity with less resource consumption are ∗ Corresponding Author: mpb1@nist.gov needed. Properly executed maintenance management procedures are one method to increase productivity through increased ma- chine life and availability, and through reduced machine failures. These maintenance management procedures are often performed on an ad-hoc basis with little influence from previous histori- cal data. This paper provides key performance indicators (KPIs) to guide maintenance management procedures using historical maintenance work order (MWO) data. The standard IEC 62264-3 defines maintenance operations management as “the collection of activities which coordinate, direct and track the functions that maintain the equipment, tools and related assets to ensure their availability for manufactur- ing and ensure scheduling for reactive, periodic, preventative, or proactive maintenance” [1]. Maintenance operations man- agement involves providing maintenance responses to equipment problems, scheduling and performing maintenance based on time or cycles of a machine or part, providing condition based main- tenance, or optimizing resource operating performance and effi- ciency. Within IEC 62264-3, a number of steps are defined for performing maintenance operations management. One step is the development and management of key performance indicators re- lated to maintenance. Key performance indicators are defined in ISO 22400-1 as a “quantifiable level of achieving a critical ob- jective”, while the elements of a KPI are defined as “relevant measurements for use in the formula of a key performance indi- cator” [2]. Maintenance KPIs aid maintenance decisions, such as “what machine to send a technician?”, “who to send to solve a problem?”, “what is the most likely cause of the problem?”, 1 Copyright c  2018 by ASME