Small batch production, rapid product turnover, and high conversion costs. Flexible production lines can meet the practical business requirements of small batches and mixed production of multiple varieties simultaneously. They achieve zero-second line changeovers and zero-second style changeovers based on order requirements.
Employee work efficiency is relatively low, making it challenging to improve efficiency through traditional means. Transportation efficiency is enhanced through smart hanging systems, and Industrial Engineering (IE) techniques are used to dynamically allocate tasks, reducing bottlenecks and idle processes, thereby increasing overall production efficiency. Data on the efficiency of each team and employee in various production processes is collected and analyzed to provide a foundation for improving employee skill levels.
Relying on increasing manpower to boost production capacity, with a relatively low level of automation, it's challenging to break through the production efficiency bottleneck. Flexibly choose to implement overall or partial smart upgrades. Tailor the level of automation and informatization to specific needs by combining or splitting software and hardware components.
Real-time data is not readily available, affecting timely production adjustment decisions. All software, hardware, and equipment data across different regions within the group are seamlessly integrated, centralized, standardized, analyzed, processed, and used for instructions. The CM Industrial Internet platform will become the most powerful decision-making, operational, and management tool for the enterprise.
Difficulty in recruiting workers and high labor costs are the main obstacles to business development. By employing various intelligent methods, we optimize handling, scheduling, management, and statistical processes, reducing the need for human resources, improving workforce efficiency, and enhancing coordination across all stages.
Bottleneck effects, occurring at any time during the production process, lead to significant production capacity wastage. Scheduling on-site is challenging. Generate human-machine placement recommendations based on big data and the actual situation of the enterprise. During task assignments, historical data on team efficiency, employee skills, and employee performance are thoroughly considered, ensuring a fair, reasonable, and optimally efficient dynamic allocation.