Work

Asset Management Excellence: A Roadmap for Integrating Lean Six Sigma and ISO 55001 to Achieve Operational Excellence

Year: 2025
Type: article
Abstract: Asset Management Excellence (AME) has become essential for sustaining operational efficiency and long-term competitiveness in today’s digitally driven and increasingly complex industrial landscape. This study introduces an integrated roadmap that aligns Lean Six Sigma (LSS)—specifically the DMAIC methodology—with ISO 55001 standards to enhance asset reliability, optimize lifecycle performance, and support continuous improvement. The proposed model embeds principles such as lifecycle value optimization, risk-based decision-making, and sustainability. It leverages proven tools, including Failure Mode and Effects Analysis (FMEA), Root Cause Analysis (RCA), Statistical Process Control (SPC), predictive maintenance, and real-time monitoring to enable proactive, data-driven asset management. This integration supports efficiency, reduces variability, and extends asset life. Performance is measured through key indicators such as Mean Time Between Failures (MTBF), Overall Equipment Effectiveness (OEE), and lifecycle cost-efficiency. These metrics enable organizations to monitor progress, validate improvements, and ensure alignment with strategic objectives. The study also addresses common implementation challenges across financial, organizational, workforce, technological, and structural domains. It proposes targeted mitigation strategies, including phased implementation, cost-benefit analyses, stakeholder engagement, digital readiness assessments, and capacity-building programs to enhance adoption and long-term sustainability. While conceptual, the roadmap offers a practical, scalable approach to embedding LSS within asset management systems. It fosters a transition from reactive to proactive practices, enhancing resilience, sustainability, and strategic value. Future research will validate the framework through sector-specific case studies and pilot implementations.
Institution: Benha University
Language: English
Open Access status: hybrid
OpenAlex ID: W4411591756
FWCI: 6.413
Cites: 11
Cited by: 7
Related to: 10