Maintenance costs are a major part of the total operating costs of manufacturing and production operations — including molding. Maintenance costs cover a wide range of both maintenance- and non-maintenance-related expenditures, including lost production time — and the costs can be significant if not well managed.
What’s more, ineffective maintenance management significantly impacts companies’ ability to manufacture quality products that are competitive in the world market. As a result, the loss of production time and product quality created by poor or inadequate maintenance management can have a dramatic impact on business success, industry reputation, and customer satisfaction.
The dominant reason for disruptive and high-cost machine maintenance is the lack of actionable data available to quantify the actual need for repair or replacement of machinery, equipment, and systems. Today, predictive maintenance technologies are addressing these problems with viable solutions. Thanks to its ability to better manage maintenance issues, predictive maintenance can lower production costs, streamline processes, and result in better quality products.
Today, predictive maintenance for injection molding machines is being enabled by smart analytics. This provides progressive molding operations and their customers with a number of valuable benefits.
A recent research study looked into the advent of bringing predictive maintenance into injection molding and came to an interesting conclusion.
Study Finds Predictive Technologies Prevent Machine Failures
Injection molding machines in the plastic processing industry have to work continuously for long hours to enable continuous production throughput. As a result, a series of predictive, preventive, and inspection activities that send alerts regarding machine problems and failures are vital for the normal and stable operation of a molding machine. Recognizing this, a team of researchers at a technology institute in Greece conducted a study to assess the real-world benefits of predictive maintenance in injection molding.
The results of the study included:
- Predictive maintenance can assist in decision support for injection molding machines maintenance to prevent failures in production and downtime of machines.
- By applying historical data and live predictions based on real-time data, the solution detected faults in different machines within a single factory.
- Ensemble methods of maintenance management can enhance the prediction models’ performance results.
- Automatic updating of trained models addresses the problem of possible deviations of new incoming machine data or potential prediction model degradation.
A1 Tool Leverages Smart Molds for Optimal Operations
A1 Tool is already on the leading edge of injection mold technology — including using smart molds. Smart molds provide real-time actionable data, including identifying past trends, future predictable outcomes, and current mold performance. This insight drives decision-making that improves mold efficiency, speed, quality production, and cost savings.
Thanks to predictive analytics, smart molds help catch errors or maintenance issues before they occur. As a result, they can be adjusted or repaired before they break down and take an entire operation offline. This capability significantly reduces costs and improves efficiency.
Smart molds also use technology to provide information on most components of molding — including repeat set-ups, pressure sensors, mold flow, cooling pressures, and mold temperatures. This data can maximize mold performance, reduce setups, and accelerate mold speed for maximum performance — all of which improve savings and the final products for our customers.
Learn more about how smart molds can make a difference in your injection mold production demands.
