Purpose: This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines. Design/methodology/approach: The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives. Findings: The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities. Originality/value: The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

(2021). Data-based decision-making in maintenance service delivery: the D3M framework [journal article - articolo]. In JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT. Retrieved from http://hdl.handle.net/10446/192303

Data-based decision-making in maintenance service delivery: the D3M framework

Sala, Roberto;Pirola, Fabiana;Pezzotta, Giuditta
2021-01-01

Abstract

Purpose: This paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines. Design/methodology/approach: The Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives. Findings: The interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities. Originality/value: The paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.
articolo
2021
Sala, Roberto; Bertoni, Marco; Pirola, Fabiana; Pezzotta, Giuditta
(2021). Data-based decision-making in maintenance service delivery: the D3M framework [journal article - articolo]. In JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT. Retrieved from http://hdl.handle.net/10446/192303
File allegato/i alla scheda:
File Dimensione del file Formato  
10-1108_JMTM-08-2020-0301.pdf

accesso aperto

Versione: publisher's version - versione editoriale
Licenza: Creative commons
Dimensione del file 1.06 MB
Formato Adobe PDF
1.06 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/192303
Citazioni
  • Scopus 19
  • ???jsp.display-item.citation.isi??? 12
social impact