A sustainable development framework for a cleaner multi-item multi-stage textile production system with a process improvement initiative

One of the most significant sectors in global economy is the textile industry, especially in asian continent. Owing to massive consumption of water in the wet processing operations of the textile sector, this industry is a major creator of effluent water. These effluents severely negatively affect plant photosynthetic function and must be treated prior to discharge into the environment. Reducing this type of hazardous environmental waste is one of the key considerations of lean philosophy. This enhances the consideration of the investments and expenditures made for waste water treatment in production decisions of the textile industry. Along with this, carbon emissions from production systems are more tightly regulated than in the past. Under emissions tax and allocated cap policies, manufacturing setups have to reduce their emissions by upgrading through technological changes and process improvements. In this context, this research provides a sustainable development framework for a cleaner textile production system (in the wet-processing category). The production model is analyzed with regard to environmental and effluent water treatment policies in the multi-stage production system, and optimal batch quantity is determined through a metaheuristic approach. Process reliability can be achieved by improving the production process, for which a discrete investment policy for setup cost reduction and process improvement is suggested, and benefits of these investments to improve environmental protection are studied through comparative analysis. Practical applicability of the proposed production model is highlighted through numerical experiment, sensitivity analysis, and important managerial insights. A trade-off among the investments in various aspects of the system is developed, and the results analysis verify that the introduction of discrete investments for process improvement reduces the effluent water quantity by 12.56% and variable CO₂ emissions cost by 20.98% per batch, thus motivating economic growth and minimizing environmental impacts of the production system.