<![CDATA[Production planning and control (PPC) in job-shop manufacturing is complicated by factors such as high product variety, small batch sizes, changing routings, and frequent disruptions. These difficulties are more severe in developing economies, where limited infrastructure, shortage specialist expertise, unreliable energy supply, and financial constraints restrict the adoption of advanced planning systems. This review critically examines the application of expert systems (ESs) to PPC in job shops. It evaluates their capacity to integrate forecasting, manpower planning, energy utilization, machine scheduling, inventory control, cost estimation, and due-date determination. The review follows a sequential process of literature identification, screening, thematic classification, quality appraisal, and synthesis. Its novelty lies in treating these PPC functions as interdependent rather than isolated decisions and in translating evidence into an explainable, feedback-based ES–PPC architecture designed for the operational realities of small and medium-sized enterprises in developing economies. The synthesis shows that existing studies generally optimize individual functions, while only a limited number integrate rule-based reasoning, optimization models, shop-floor data, and performance feedback within a unified framework. The review therefore proposes an integrated architecture and identifies priorities for real-time adaptation, low-cost deployment, explanation of recommendations, and validation with shop-floor data. These contributions provide a structured foundation for the development of practical ES-enabled PPC systems for job-shop manufacturing.]]>
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