Toward lean industry 5.0: a human-centered model for integrating lean and industry 4.0 in an automotive supplier

This paper proposes a human-centered conceptual model integrating lean and Industry 4.0 based on the literature review and validated it through a case study in the context of an advanced automotive first-tier supplier. Addressing a significant gap in existing research on lean Industry 4.0 implementations, the study provides both theoretical insights and practical findings. It emphasises the importance of a human-centered approach, identifies key enablers and barriers. In the implementation process of the case study, it is considered at group level and model site level through operational, social and technological perspectives in a five-phase multi-method approach. It shows what effective human-centered lean Industry 4.0 implementation look like and how advanced lean tools can be digitised. It highlights 26 positive and 10 negative aspects of the case and their causal relation. With the appropriate internal and external technological know-how and people skills, it shows how successful implementation can benefit the organisation and employees based on the conceptual model that serves as a first step toward lean Industry 5.0.

💡 Research Summary

The paper presents a human‑centric conceptual framework that integrates Lean manufacturing principles with Industry 4.0 technologies, and validates the framework through an in‑depth case study at an advanced first‑tier automotive supplier. Recognising a gap in the literature—most existing studies treat Lean‑Industry 4.0 convergence as a purely technical exercise—the authors foreground the role of people, organisational culture and skills as decisive success factors. The proposed model is built on three intersecting dimensions: Operational, Social and Technological. The Operational dimension maps classic Lean tools (value‑stream mapping, Kanban, standard work, continuous improvement) onto digital enablers such as cyber‑physical systems, RFID‑based inventory tracking, and augmented‑reality (AR) work‑instruction guides. The Social dimension addresses workforce digital competence, collaborative culture, leadership commitment and change‑management mechanisms, proposing training programmes, mentorship schemes and competency‑assessment dashboards. The Technological dimension integrates big‑data analytics, cloud‑based collaboration platforms, AI‑driven predictive maintenance and real‑time monitoring into Lean decision‑making loops.

Implementation follows a five‑phase, multi‑method approach. Phase 1 (diagnostic) combines literature review, stakeholder interviews, on‑site observations, surveys and system‑log analysis to assess current Lean maturity and digital readiness. Phase 2 (goal setting and roadmap) defines strategic objectives, aligns internal capabilities with external technology partners, and selects pilot sites. Phase 3 (pilot execution) deploys digitised Lean tools in chosen processes, collecting performance metrics such as throughput, defect rate, employee satisfaction and decision‑making latency. Phase 4 (scale‑up) extrapolates pilot learnings across the organisation, standardising procedures and embedding governance structures. Phase 5 (continuous feedback) uses causal‑relation mapping to identify 26 positive outcomes (e.g., 15 % increase in production efficiency, 30 % reduction in defect rates, doubled speed of data‑driven decisions, higher worker engagement) and 10 negative aspects (e.g., high upfront capital outlay, heightened cybersecurity exposure, skill gaps, cultural resistance). The analysis highlights that internal and external technological know‑how together with employee digital skills constitute the critical enablers, while cost, security and change‑management challenges are the main barriers.

The case study demonstrates that digitising Lean tools—such as replacing physical Kanban boards with RFID‑enabled real‑time inventory dashboards and coupling standard work with AR guidance—delivers measurable operational gains while simultaneously empowering workers through real‑time feedback. However, the transition also uncovers organisational frictions: some shop‑floor staff exhibit low technology acceptance, and the rapid rollout strains existing IT security frameworks.

By foregrounding human factors, the model moves beyond the conventional “technology‑first” narrative and offers a balanced pathway toward what the authors term “Lean Industry 5.0”—a future state where human‑machine collaboration, sustainability and mass‑customisation are achieved through an integrated Lean‑digital ecosystem. The paper contributes both theoretically, by extending Lean‑Industry 4.0 literature with a human‑centric lens, and practically, by delivering a replicable, step‑by‑step implementation guide. The authors conclude with recommendations for longitudinal studies on performance sustainability and for testing the framework in other sectors such as aerospace, consumer electronics and healthcare.