Medical manufacturers face many of the same challenges most heavy industrial businesses are currently dealing with—rising costs, labor shortages, and ongoing supply chain uncertainty.

Industry 4.0 technology can be an invaluable asset for these companies. It can be used to improve almost every aspect of medical manufacturing.

These technologies are some of the most important to medical manufacturers right now. They could soon transform an industry that is adapting to a changing market.

New Approaches to Automation with Robots

Like many other industries, medical device manufacturing faces a significant labor shortage. This means manufacturers must adapt their workflows to increase productivity without hiring additional workers.

Modern robotics can offer new solutions for medical device manufacturers—even those that have already invested heavily in conventional robotics. For example, a company may need to sharpen and deburr loads of sharps for use in a particular product. A six-axis robot, integrated into a grinding workcell, may be able to automate many tasks involved in the loading and unloading of sharps into machine fixtures for sharpening and deburring.

Another manufacturer may need to entirely automate sealing very small and irregularly shaped containers for a product. Consistency of demand and volume of sales may make the cost of automation worth it. A packaging robot may help reduce labor costs, increase productivity, and mitigate the risk of certain errors.

Other common use-cases of modern plant robots include product assembly, quality control, and pick-and-place operations. Some cutting-edge medical manufacturing robots incorporate technology like artificial intelligence (AI), which can enable additional applications or make the robot more versatile.

However, some workflows may require robots that slot into existing work, supporting human staff in operating machines or performing critical manufacturing tasks.

Using Collaborative Robots in Medical Device Manufacturing

Manufacturing automation doesn’t have to mean replacing human labor entirely, even on the plant floor. Many medical device manufacturers are also beginning to rely on collaborative robotics (cobots)—specialized robots built to work alongside people. This frees them for more complex tasks while also improving efficiency and reducing the risk of error.

Cobots allow humans and robots to work side by side. These machines feature padded joints, force limiters, and even machine vision technology that lets robots dynamically observe and respond to their environment. That mitigates many of the safety risks.

Cobots typically occupy a much smaller footprint and weigh much less than conventional robots. They are easy to reprogram and reposition in many cases, making it possible to use one machine for many different purposes with minimal retooling and setup time.

For example, a medical device cobot could handle most of the heat sealing process for a medical product. It could load trays and lids from tabletop heat-sealing machines, initiate the heating process, and remove sealed packages from the device.

Other use-cases of cobots include machine tending, packaging, palletizing, and quality inspection. As cobot technology improves, additional use-cases are likely to become available.

Cobots help manufacturers do more with available labor by supporting rather than replacing human workers. They can accelerate certain tedious or easy-to-automate tasks, freeing plant staff up for work that requires creativity and problem-solving skills.

AI-Powered Anaytics and Forecasting

Medical device manufacturers have access to more data than ever. However, it can be challenging to leverage that information effectively due to the sheer volume available.

AI is a data analysis tool that can power algorithms to uncover insights and patterns that more conventional methods of analysis might miss. As a result, many businesses are beginning to use AI for manufacturing analytics and forecasting purposes.

The right AI algorithms and other analytic tools help manufacturers improve data visibility, increase plant flexibility, and streamline decision-making. Data dashboards can make it much easier for managers to quickly review KPIs or essential metrics and develop a big-picture view of current plant operations. This information visibility makes it easier to prescribe action to factory employees or spot potential bottlenecks in plant operations.

An AI algorithm can also directly improve the manufacturing process. The right AI tool can analyze the manufacturing process and its outcomes to identify how variables like equipment settings or environmental conditions may be affecting product quality.

At the organizational level, AI forecasting algorithms can also help managers predict and respond to inventory shortages, changing consumer demand, and sudden supply chain crises. Sales data and market research makes it possible to predict a wide range of market conditions—helping the business manage risk and better prepare itself for future uncertainty.

Improving Data Collection and Visibility

Medical device manufacturers can benefit more from effective data collection with the power of AI and other advanced analytic technologies.

Internet of Things (IoT) devices have emerged as one of the most valuable data-gathering tools businesses have access to. They can collect information on a wide range of plant processes—including equipment performance, the movement of essential assets and worker productivity.

Many IoT devices can also enable the remote management and monitoring of essential equipment. They allow workers to track or control the performance of individual machines and autonomous cells in a device manufacturing plant.

Like data dashboards, these devices can also provide managers with a bird’s-eye view of plant operations. IoT asset trackers, for example, make it easy to visualize the flow of important raw materials, products, and components around a plant. This information can make process bottlenecks or inefficiencies much easier to spot.

Combined with AI, IoT can also enable new, more advanced upkeep and repair practices. Predictive maintenance uses AI and IoT data on equipment performance to forecast when machines will need tune-ups or repair.

Identifying patterns in equipment operating parameters like speed, temperature, timing, and vibration allows a predictive maintenance algorithm to predict failure states or upkeep requirements. It can help manufacturers reduce maintenance costs, mitigate downtime, and keep plant equipment running for longer.

How Businesses Can Leverage Medical Device Manufacturing Advances

The right technology can improve almost every aspect of medical manufacturing—from plant processes to big-picture decision-making.

New robots and IoT systems can enable manufacturers to automate work that typically requires human labor, freeing employees for more important tasks. The predictive powers of AI can help companies cope with an uncertain market and supply chain instability.

These technologies will likely benefit the medical manufacturing industry as they become more sophisticated.

Article source: Medical Product Sourcing