Data-driven strategies for service efficiency and spare parts management in industrial moulding maintenance

Abstract

Objectives: This study analyzes the relationship between service productivity, spare parts sales, and corporate revenue in industrial plastics equipment maintenance using a real-world case study. The research quantifies the correlation between key performance indicators (KPIs) and a company's financial performance. It also investigates how quality management tools, like the Ishikawa diagram and FMEA, can identify and prioritize operational inefficiencies. The objective is to provide actionable strategies to improve resource allocation, optimize scheduling, and enhance service profitability.

 Implication: The study shows that spare parts sales are the primary driver of service revenue (correlation 0.96) and engineer productivity is strongly linked to service revenue (correlation 0.88). The findings highlight a strategic misalignment where overall company growth is driven more by equipment sales than services. Using FMEA, the research identifies critical risks such as limited stock availability (RPN: 504), high employee turnover (RPN: 336), and long lead times (RPN: 336). These insights offer a clear pathway for companies to transform service divisions into strategic growth engines by addressing these inefficiencies.

 Originality value: This research provides a unique contribution by integrating quantitative and qualitative data in a real-world case study. The paper combines historical financial data with structured quality management methodologies like the Ishikawa diagram and FMEA. This approach creates a replicable framework for diagnosing operational weaknesses and prioritizing corrective actions. By moving beyond simple correlation, the study identifies specific, high-risk failure modes and offers targeted recommendations, bridging the gap between academic theory and practical business strategy.