Abstract
PurposeThis 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/approachThe 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.FindingsThe 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/valueThe 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.
Highlights
Recent technological evolution has increased competitiveness in the manufacturing sector, forcing companies to find new ways to create long-term relationships with customers who are always more eager to buy products and services tailored to their necessities and requirements
The D3M framework contributes to the research related to the definition of procedures that can guide companies and practitioners in collecting and exploiting data generated during maintenance service delivery and machine working time
The framework answers RQ1 by identifying the phases for data collection and analysis on the machine and service sides, the actors involved in the process and the decisions to be addressed
Summary
Recent technological evolution has increased competitiveness in the manufacturing sector, forcing companies to find new ways to create long-term relationships with customers who are always more eager to buy products and services tailored to their necessities and requirements. This transition poses several challenges related to the network organization, the stakeholders’ integration and interaction, the way customers experience products and services and the management of all the resources involved in the PSS contract (Meier et al, 2011; Wuttke et al, 2019). This is emphasized, for instance, when customers interested in machines’ availability use different indicators linked to maintenance (e.g. downtime, responsiveness) to select the provider and evaluate the service quality (Sheikhalishahi and Torabi, 2014)
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