制药生产中低效机器控制的隐性成本：Beckhoff UK & Ireland 谈智能控制与数据分析

12 October 2026

11:00

Pharmaceutical manufacturers face constant pressure to increase productivity while maintaining the quality, consistency and traceability demanded in highly regulated production environments. Beth Ragdale, product manager at industrial control and automation specialist Beckhoff UK & Ireland, discusses.

As a result, many focus their investments on visible hardware upgrades, whether it’s replacing motors with higher-efficiency alternatives, upgrading drives or redesigning mechanical systems. These improvements can make a difference, but often the greatest gains don’t come from replacing physical components.

The pharmaceutical sector continues to embrace automation to improve production efficiency while ensuring compliance with strict regulatory requirements. Today’s facilities must manufacture increasingly complex products, such as sterile injectables, biologics and advanced therapies, support batch production across multiple batch sizes and product variants and generate operational data that helps demonstrate process consistency and enable continuous improvement.

Replacing motors and upgrading mechanical components is important here but is unlikely to unlock the next step change in efficiency alone. Achieving this requires intelligent control of the machines on the production line.

Control as the foundation of efficiency

Machine control plays a key role in determining how effectively a system operates. Even the most efficient hardware can underperform if control logic results in unnecessary movements, excessive cycle times or machines running when not adding value.

Inefficient sequences, poorly optimised motion profiles and excessive machine idle time can all introduce hidden costs for manufacturers. For example, an automated pick-and-place robot transferring vials or syringes between production stages may complete thousands of precise movements each day. However, if the robot travels further than necessary between operations or waits unnecessarily for other processes to complete, even those small inefficiencies can snowball into significant losses in cycle time and energy consumption.

By introducing more intelligent control architectures, manufacturers can optimise these processes at source. Integrated automation platforms allow motion, logic, safety, measurement and data acquisition to work together, resulting in a more coordinated approach to machine operation.

Rather than simply instructing a production machine or robot to complete a task, modern control systems can analyse how that task is performed and identify opportunities to improve performance. This may include reducing unnecessary axis movement, adjusting machine parameters dynamically or coordinating different parts of a production cell more effectively.

Continuously optimising with data

As more machine data becomes available, this creates fresh opportunities for manufacturers to optimise performance beyond traditional automation approaches, which often prioritise programming machines to complete predefined tasks efficiently. By capturing information from machines in real time, engineers can better understand how their equipment operates and identify areas for improvement.

Beckhoff developed TwinCAT® Analytics to help manufacturers analyse their machines’ operational data and uncover patterns and inefficiencies that may not be immediately obvious. By examining factors such as cycle times, energy consumption and machine behaviour, TwinCAT Analytics’ out-of-the-box algorithms can help identify bottlenecks, excessive idle time and inefficient operating stations, allowing manufacturers to make evidence-based decisions to improve processes and maximise equipment performance.

Importantly, this data supports condition monitoring strategies by highlighting changes in machine behaviour before they lead to unexpected issues. For example, by identifying changes in vibration, temperature or operating patterns, maintenance teams can address potential problems earlier, minimise unexpected disruptions and support more predictable production.

Automated systems used across pharmaceutical production, such as robotic handling systems and inspection equipment, may be required to operate reliably for extended periods. In these settings, even small inefficiencies can become significant over time. The way machines are controlled, monitored and optimised is just as important in determining their overall performance. By combining intelligent automation with real-time data analysis, pharmaceutical manufacturers can improve productivity, reduce unnecessary energy consumption and extend their equipment’s operational life while supporting the precision, consistency and reliability needed.