The practical applications of integrated maintenance policies and quality for a multi-component system are more complicated, still rare, and incomplete to meet the requirements of Industry 4.0. Therefore, this work aims to extend the integration economic model for optimizing maintenance policies and quality control parameters by incorporating the Taguchi loss function for a multi-component system. An optimization model is developed based on preventive maintenance, corrective maintenance policies, and quality control parameters with the CUSUM (Cumulative Sum) chart, which is widely used for detecting small shifts in the process mean. The model was developed to minimize the expected total cost per unit of time and to obtain the optimal values of decision variables: the size of samples, sample frequency, decision interval, coefficient of the CUSUM chart, and preventive and corrective maintenance intervals. The solution steps were employed by selecting a case study in the Alahlia Mineral Water Company (AMWC). Then, the design of experiments based on one-factor-at-a-time was used to evaluate the effect of selected decision variables on the expected total cost. Finally, sensitivity analysis was performed on the selected decision variables to demonstrate the robustness of the developed model. A predictive maintenance plan was developed based on the optimal value of preventive maintenance interval, and the results showed that the performance of the maintenance plan realizes the full potential of the integrated model. In addition, the case study results indicate that the extended integrated model for multicomponent is the new standard for the quality production of multi-component systems in future works.

Food manufacturing facilities are a crucial industry for many national economies. However, maintaining a sterile, clean environment they require also demand large amounts of energy and fuel, necessitating in-depth scientific studies to conserve energy in such complex environments. This study designed a unique, large-scale, and industrial-level waste heat recovery (WHR) system with an 18-month implementation within 15 tunnel ovens at a Biscuits and Wafers Industry (BWI) plant in Yemen, a country facing multiple energy challenges. Initial measurements indicated that up to 60% of thermal energy was delivered within the exhaust gases at 150–250 ℃, with a cumulative waste energy of up to 6,000 MWh/year. To overcome this, modular heat pipe systems with deionized water and a sintered copper wick were incorporated to preheat combustion air. Material integrity was verified through Helium leak testing (<1*10−9 mbar*L/s) and monthly ATP bioluminescence swabbing (<10 RLU), providing empirical evidence of zero cross-contamination and HACCP compliance. The proposed system had thermal efficiencies (η) of 36–42%, and exergy efficiencies (ψ) of 22–28%, indicating that an energy saving of more than 3,000 MWh/year and a reduction of about 650 t CO2 emissions could be achieved. Economic analysis resulted in a very competitive simple payback period of 4.1–4.6 years and an Internal Rate of Return (IRR) of 20–22.3%. Besides, the proposed design also offers validated design parameters and SCADA-based control strategies to scale up carbon-neutral thermal recovery in the global food manufacturing industry. It also provides economic standards and operational values for wider industry applications.