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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.

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.

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.

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.

Nowadays manufacturers companies are increasingly compelled to navigate towards servitization. Different methods and approaches were proposed in literature to support them to switch from traditional product-based business model to product service systems (PSSs). However, new knowledge, capabilities and skills were needed to consistently develop PSSs, since they need a joint focus on both customer’s perspective and company’s internal performance and at the same time a proper support for the integration of product and service design. The purpose of this paper is to propose the Product Service System Lean Design Methodology (PSSLDM), a structured methodology to develop PSSs along their entire lifecycle.

Retrieving concepts from interpretative, interactive and system development research traditions, and strongly reminding the design research methodology framework, the adopted research methodology is composed of three main phases (observation and conceptualization, theory building and tool development, validation) and involved three heterogeneous companies.

This paper provides an overview of the PSSLDM, explaining how the different methods supporting its conduction should contribute to properly design an integrated PSS. Moreover, companies highlighted several benefits in the different stages along the PSS lifecycle deriving by the adoption of the PSSLDM.

The development of a platform based on the PSSLDM methodology raises a discussion on the possible changes needed by current Product Lifecycle Management (PLM) models and systems when they have to do with PSSs.

The PSSLDM enriches the already proposed SErvice Engineering Methodology, introducing new several components linked by lean rules in each of its phases (starting from customer analysis, going through solution concept and detailed design, until the offering analysis) and better supprting the deatil design of both prodcut and service components.

Given the challenges that Industry 4.0 poses, the purpose of this paper is to propose a comprehensive assessment model suitable for evaluating small- and medium-size enterprises’ (SMEs) digital readiness levels, discuss the results of an assessment of 20 manufacturing SMEs using the proposed model and highlight priorities needed to undertake a successful journey towards Industry 4.0.

The research adopts an empirical approach using multiple case studies. Starting with a literature review about maturity and readiness-assessment models for Industry 4.0, the study’s model has been built and validated through two pilot case studies, with the final model used in an extensive case studies research with 20 enterprises.

The SMEs used in this research present an intermediate readiness level with respect to Industry 4.0. They are aware of the phenomenon, but management is still taking the first steps towards identifying the most appropriate strategy to approach this Fourth Industrial Revolution. Companies need to exploit all opportunities that data availability provides in terms of knowledge creation and decision-making support, in all forms, through investments in people skills and expertise and through an infrastructure that can support data gathering, analysis and sharing.

The Italian industrial landscape comprises mainly SMEs, mostly needing support to understand their path towards Industry 4.0. Therefore, the proposed model specifically focuses on SMEs, given its modularity, ease of understanding and fit to SMEs’ organisational structure. Furthermore, insights from 20 Italian SMEs are examined, and a list of priorities is highlighted.