Faculty Publications

Smart Maintenance Decision Support Systems (SMDSS) Based On Corporate Big Data Analytics

Document Type

Article

Keywords

Analytical modeling, Asset management, Big data, Decision Support Systems, Maintenance

Journal/Book/Conference Title

Expert Systems with Applications

Volume

90

First Page

303

Last Page

317

Abstract

The purpose of this article is to outline the architectural design and the conceptual framework for a Smart Maintenance Decision Support System (SMDSS) based on corporate data from a Fortune 500 company. Motivated by the rapidly transforming landscape for big data analytics and predictive maintenance decision making, we have created a system capable of providing end users with recommendations to improve asset lifecycles. Methodologically, a cost minimization algorithm is used to analyze a large industry service and warranty data sets and two analytical decision models were developed and applied to a case study for an electrical circuit breaker maintenance problem. Some of these techniques can be applied to other industries, such as jet engine maintenance, and can be expanded to others with implications for robust decision analysis. The SMDSS provides a predictive analytical model that can be applied in manufacturing and service based industries. Our findings and results show that existing solution algorithms and optimization models can be applied to large data sets to lay out executable decisions for managers.

Department

Department of Management

Department

Department of Accounting

Original Publication Date

12-30-2017

DOI of published version

10.1016/j.eswa.2017.08.025

Repository

UNI ScholarWorks, Rod Library, University of Northern Iowa

Language

en

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