Manufacturing organisations, particularly small and medium-sized enterprises, face challenges in coordinating production and maintaining consistent quality in job-shop environments characterised by high product variety and short life cycles. This study presents an integrated framework combining production planning, value stream mapping (VSM), multi-criteria decision-making (AHP), and statistical process control (SPC) to improve operational efficiency and process performance. A case study in a job-shop manufacturing system demonstrates how AHP prioritises production planning criteria and identifies the most suitable strategy, while VSM visualises material and information flow to highlight bottlenecks. SPC techniques, including control charts and process capability analysis, are applied to monitor and stabilise production processes, reducing variation and improving quality. Results indicate that the hybrid production planning system outperforms conventional push and pull strategies, and the systematic application of SPC reduces process variability, enhancing product consistency. The framework provides a structured, practical approach for small manufacturers to integrate planning and quality control, offering significant improvements in throughput, lead time, and product reliability. The study highlights the potential of combining relatively simple engineering tools in a systematic manner to achieve measurable performance gains in complex job-shop operations.

Keywords

Job-shop manufacturing, Production planning, Value Stream Mapping (VSM), Analytic Hierarchy Process (AHP), Statistical Process Control (SPC)