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Predictive maintenance (PdM) has attracted increasing attention in recent years owing to the emergence of advanced condition-monitoring technologies and data analytics tools. However, the application of PdM in spare parts inventory management across the supply chain (SC) has not been sufficiently investigated and its digital transformation (DT) requirements have not been adequately researched. Therefore, this study aims to analyse the organisational readiness for the use of integrated spare parts inventory management together with PdM systems across the SC.

A series of semi-structured interviews were designed and took place across organisations in various industries to address the pre-defined research aim. In total, 15 interviewees were recruited through purposive sampling, including managers and technicians in various organisations from different industries.

The findings reveal that while maintenance planning and optimisation has been the subject of extensive research for decades, manufacturers are still encountering barriers in adopting and implementing digital innovations. The experts also highlighted the need for an integrated information system (IS) enabling data sharing across the organisation since lack of integration has a vital impact on the overall business and operations performance as well as the successful DT of the enterprise. In addition, they report that the necessary and relevant data for implementing PdM is not captured or stored in their organisations.

The present study emphasises the technical, organisational, and environmental (TOE) dimensions that can affect such DT and sheds light on the enablers and inhibitors that organisations face in their efforts to be technologically ready to embrace the digital integration of PdM with spare part inventory management. It is recommended that a clear shift in management mindset and organisational culture is necessary for companies to realise the benefits of PdM and the DT that will result from its implementation.

This study aims to assess the feasibility and effectiveness of incorporating predictive maintenance (PdM) into existing practices of spare part inventory management and pinpoint the barriers and identify economic values for such integration within the supply chain (SC).

A two-staged embedded multiple case study with multi-method data collection and a combined discrete/continuous simulation were conducted to diagnose obstacles and recommend a potential solution.

Several major organisational, infrastructure and cultural obstacles were revealed, and an optimum scenario for the integration of spare part inventory management with PdM was recommended.

The proposed solution can significantly decrease the inventory and SC costs as well as machinery downtimes through minimising unplanned maintenance and addressing shortage of spare parts.

This is the first study with the best of our knowledge that offers further insights for practitioners in the Industry 4.0 (I4.0) era looking into embarking on digital integration of PdM and spare part inventory management as an efficient and resilient SC practice for the automotive sector by providing empirical evidence.

This study aims to explore the potential application of blockchain technology in Lean Six Sigma (LSS) project through a proposed blockchain-LSS (BLSS) model. The proposed model can tackle real-time problems in information sharing, transparency and traceability in every stage of the LSS project.

The scoping review approach is used to develop the integrated model of the BLSS approach for operational excellence. The proposed model is validated through expert’s input, which is collected by a questionnaire survey method.

The prime function of the proposed BLSS model is the information sharing among the project team and real-time monitoring, transparency, traceability and immutability in the Define-Measure-Analyze-Improve-Control phase. The proposed model also consists the information about the role of blockchain features at each phase of the LSS project. The project team and industry employees can trace the success of the project at every moment, resulting in trust buildup and the elimination of fake data. Moreover, there would be no disputes among various sections/shops of the plant and employees to share the real information.

This paper provides guidelines to practitioners and managers for integrating the LSS approach and blockchain. The blockchain helps managers and practitioners in better data traceability and transparency, monitoring of data as well as more sustainable LSS project management.

To the best of the authors’ knowledge, this is the first research attempt that developed an integrated model of blockchain and LSS approach to maintaining the immutable records of assets in projects and targeted Industry 4.0.

The purpose of this study is to apply bibliometric techniques to critically examine the contributions of Professor (Dr) Jiju Antony in the domain of quality management research over a period close to 30 years (i.e. 1995 to 2023).

The study incorporates a bibliometric analysis approach using VoSviewer software package to critically examine the contributions and trends in publications on Scopus indexed publications of Antony, followed by an industry wide evaluation of contributions made. Thematic analysis of the bibliographic data was imported in comma-separated values (CSV) format by selecting Antony (last name) and Jiju (first name) in the author search tab in Scopus. The search was made on September 09, 2023 and bibliographic records of 429 documents were considered for the analysis. The analysis was carried out in terms of most frequent keywords used, sources with most frequent publications, thematic analysis of most cited works and global collaborations.

Antony has focused his research interest largely in the domain of quality management, publishing his research in top rated journals in the domain with a broad network of international collaborators. Antony has received 18,802 and 40,947 citations in Scopus and Google Scholar, respectively. This signifies the impact that Antony has created through his research publications. His major contributions are on the topics of six sigma, lean six sigma, continuous improvement, critical success factors and quality management practice implementations in various organizations. Diverse methodologies both qualitative and quantitative were utilized to conduct his research. However, his body of work is not without criticism. Such criticism includes the limited scope of work, with narrow focus on ISO 9001 and QMS standards, Total Quality Management (TQM). Critique also highlights the necessity for more depth, following insufficient exploration of distinctions between TQM and operational excellence (OPEX) methodologies like lean, six sigma, kaizen and agile. Antony’s work has yet to consider a diverse range of industry sectors, in terms of implementation of quality management principles, geographical location, the impact of national culture on corporate performance and explore data quality influence on decision-making. Notably, there is clear opportunity to consider the service sector in future research.

To best of the authors’ knowledge, there are few previous studies conducted using bibliometric analysis for analyzing the work of an individual. Therefore, the present study aims to set a trend whereby bibliometric analysis can be used to recognize and critically asses the contributions of other researchers in their respective domains.

Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained.

Actually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs.

An example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented.

To the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.