Cost management

Today, management requires a new approach in the areas of production planning and operations process with a cost management approach. Organizations and industrial units to lead their lives, by recognizing the impact points of the challenges ahead and positive impact, guide and lead them to advance the goals of the organization. Economic dispatching with particle swarm optimization algorithm approach is an approach in the field of industrial units. Dispatching tries to determine the share of production capacity in a way that optimizes the overall performance of the system economically and improve system performance, including: production and process planning, supply and demand balance, cost management, productivity growth, optimal allocation of resources according to the capacity of tanks, formulation of production and operational strategies, the impact on the strategic vision document. In this research, an attempt has been made to perform economic dispatching with the approach of particle swarm optimization algorithm with hypothetical information to measure the feasibility of implementation and its impact on the overall performance of the system and production process and operations.

This study aims to investigate the role of digital twins in enhancing the efficiency, quality, and competitiveness of small manufacturers, identifying key motivations, impacts, challenges, and future benefits. This qualitative study employed semi-structured interviews to gather in-depth insights from 28 key stakeholders in small manufacturing businesses that have implemented digital twin technology. Participants included business owners, operations managers, and IT specialists. The data were transcribed and analyzed using NVivo software, following a thematic analysis approach to identify and categorize recurring themes and concepts. The analysis revealed four main themes: Adoption of Digital Twins, Impact on Manufacturing Efficiency, Challenges and Barriers, and Future Outlook and Benefits. Key motivations for adoption included cost reduction, efficiency improvement, and competitive advantage. Digital twins significantly enhanced manufacturing efficiency through process optimization, quality control, and cost management. Major challenges encompassed technical barriers, financial constraints, organizational resistance, and regulatory issues. The future outlook for digital twins was positive, with potential long-term benefits and advancements in AI and IoT expected to further enhance their capabilities. Digital twins offer substantial benefits for small manufacturing businesses, including improved efficiency, quality control, and cost management. However, successful implementation requires addressing technical, financial, and organizational challenges. With continued technological advancements and strategic support, digital twins are likely to become integral to small manufacturers, driving innovation and competitiveness in the industry.