Abstract
The study addresses the critical need for on-time delivery in the make-to-order manufacturing of mining equipment, emphasising its importance for competitive advantage in a highly customised and competitive global market. Make-to-order manufacturers face challenges such as insufficient lead time, pre-production delays, sequencing problems, and shop floor overload, which impact delivery performance and customer satisfaction.
A qualitative research approach was used, involving literature review and analysis of secondary data from various manufacturing models. The study reviews traditional models like Material Requirement Planning, Just-in-Time manufacturing, Kanban, and Drum-Buffer-Rope, as well as innovative models including Lean Six Sigma, Agile Manufacturing, Demand-Driven Material Requirements Planning, and Advanced Planning and Scheduling systems. The study highlights the integration of digital transformation and artificial intelligence as a promising approach to enhance responsiveness and efficiency.
Findings indicate that hybrid models combining traditional planning, lean principles, and digital tools offer the best results in enhancing flexibility, operational agility, supply chain integration, and delivery reliability. Key constructs identified include hybrid integration, operational agility, dynamic adaptability, real-time supply chain coordination, and digital optimisation enabled by artificial intelligence.
The study concludes that a hybrid, digitally enabled on-time delivery model leveraging lean and quality methodologies, real-time data, and artificial intelligence-driven planning is most suitable to improve delivery lead times and competitiveness in make-to-order mining equipment manufacturing. Implementation of such a model supports efficient production, reduces costs, and enhances customer satisfaction, ultimately strengthening market position.