The necessity of optimum safety stock is really essential for any smart production system. For this reason, the effect of autonomation policy makes a big difference with the basic traditional automation policy. Basically, for a long-run production system, a process may transfer to an ‘out-of-control’ state from an ‘in-control’ state due to labour problems, machinery problems, or any kind of energy problems. During this ‘out-of-control’ state, machines produced imperfect items instead of perfect items. As a result, an inspection is required to identify the imperfect ones. Until now, this inspection has been utilised by human beings through the traditional automation policy and inspection errors may occur. To perform an error-free inspection, an autonomation policy is examined in this model to detect imperfect items from the production process, which makes the process smarter. The defective rate is random and follows a certain distribution. A budget and a space constraints are adopted, which makes the model non-linear with a constraint problem. Contradictory to the existing literature, the demand is price- and quality-sensitive together in a smart production system. To solve this non-linear problem with an optimised value of backorders, number of delivery lots, safety factors, and collection rate, a non-linear optimisation technique (Khun–Tucker optimisation technique) is employed. A numerical example and sensitivity analysis are provided to illustrate the model. The result finds that the optimum autonomation policy can save work-in-process inventory at the optimum value of the decision variable in the proposed model.

Incorporation of sustainable management for the rework of defective items brings long lasting benefits. In global business, there are situations when the products are procured from a global supplier. There are chances that the received lot may contain a fraction of imperfect products. These imperfect products are still valuable and can be repairable to save the environment. It is sustainable to repair imperfect items in a local repair store as compared to sending it back to the supplier. The cost of carbon emissions is also incorporated in the function to incorporate the environmental impact on total profit. Meanwhile, the supplier also offers a multi-trade-credit-period to the buyer. The developed model is sustainable and reduces the environmental impact as well as benefits for interim financing. This paper has an objective to maximize the total profit by developing a synergic economic order quantity model by considering multi-trade-credit policy, rework, and shortages simultaneously. This model can help in making decisions to enhance the performance of sustainable inventory management by controlling the cycle time and a fraction of time for a global supply chain. A non-derivative approach is employed to develop a closed-form optimal result. The numerical illustration with sensitivity analysis is also drawn to provide managerial insights into real practices.