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Research Papers

Development of a Key Performance Indicator Assessment Methodology and Software Tool for Product-Service System Evaluation and Decision-Making Support

[+] Author and Article Information
Dimitris Mourtzis

Department of Mechanical Engineering
and Aeronautics,
University of Patras,
Patras 26504, Greece
e-mail: mourtzis@lms.mech.upatras.gr

Anna-Maria Papatheodorou

Department of Mechanical Engineering
and Aeronautics,
University of Patras,
Patras 26504, Greece
e-mail: papatheodorou@lms.mech.upatras.gr

Sophia Fotia

Department of Mechanical Engineering and
Aeronautics,
University of Patras,
Patras 26504, Greece
e-mail: fotia@lms.mech.upatras.gr

1Corresponding author.

Contributed by the Computers and Information Division of ASME for publication in the JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING. Manuscript received December 22, 2017; final manuscript received May 15, 2018; published online July 3, 2018. Assoc. Editor: Kristina Wärmefjord.

J. Comput. Inf. Sci. Eng 18(4), 041005 (Jul 03, 2018) (13 pages) Paper No: JCISE-17-1307; doi: 10.1115/1.4040340 History: Received December 22, 2017; Revised May 15, 2018

During the last decade, as a result of their constant urge to retain sustainability, companies have shifted to the product-service system (PSS) business model, in an effort to gain competitive advantages. PSS providers have realized the importance of offering highly perceived solutions; thus, the necessity of monitoring the performance of PSSs and evaluating them has intensified. However, not much work has been conducted toward that direction, especially focusing on its practical application. In the current work, a holistic approach for PSS evaluation using key performance indicators (KPIs) is proposed, extending to all its lifecycle phases and covering aspects from both provider's and customer's perspectives. A software tool was developed to assist the decision maker in the selection of appropriate KPIs to monitor for PSS evaluation and additionally, to offer KPIs data collection, storage, processing, and visualization capabilities. The proposed methodology was applied in a real industrial case of the mold making area to validate its results.

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Figures

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Fig. 1

Frequency of tools used for performance management [4]

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Fig. 2

Steps of proposed KPI selection methodology

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Fig. 3

Goal categories for PSS evaluation

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Fig. 4

Conceptual design of KPI assessment tool for PSS

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Fig. 5

System architecture of developed software

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Fig. 6

Enhanced entity relationship diagram of the KPI assessment tool

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Fig. 7

Screenshot sequence of the KPI assessment tool's sub-module of KPIs management: (1) KPIs library, (2) PI definition dialog, (3) PIs-for-assessment pool, and (4) UT criteria weights setting

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Fig. 8

Objective tree of mold maintenance company

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Fig. 9

Screenshot of the KPI assessment tool's submodule of KPIs monitoring (my dashboard), displaying selected KPIs in the dashboard for mold industry

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