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Results-Driven Approach to Improve Productivity and Quality in Injection Molding

Results-Driven Approach to Improve Productivity and Quality in Injection Molding SensoNODE Gold Quick Coupling DivisionLighter, versatile, non-corroding and cost-effective. These are some of the advantages as to why manufacturers are increasingly replacing metals with plastics for product development. Plastic injection molding is a key component in a shifting manufacturing landscape and has grown beyond specialty applications. Today, it’s a sophisticated process for producing parts requiring machinery and tooling of increasing complexity. As a result, injection molding operations are being pushed to the limits at a time when product quality and manufacturing efficiency is crucial to success.  

 

Injection molding defects

Injection molding processes are exposed to a variety of potential risks over the course of production. From running unattended for long periods to equipment performance faults, operating without production monitoring can lead to real business headaches. Even the smallest of deviations or errors can impact an organization’s bottom line and result in significant ramifications including line downtime, increased scrap, late shipments and the biggest factor of all, a dissatisfied customer.

There are many variables affecting the injection molding process and each impacts product quality. The variations in temperature, humidity or mechanical pressure can lead to process or machine breakdown. By regularly monitoring the status and condition of processes and equipment, you’re able to identify potential problems and select a course of action to rectify it.

 

Implementing condition monitoring

A continuous condition monitoring program provides a valuable amount of information for predicting machinery failure or process variation aiding in the analysis of the root cause of the problem. This solution provides reliable and useful data to assess the health and condition of injection molding machines and processes.

Results-Driven Approach to Improve Productivity and Quality in Injection Molding Quick Coupling Division

The following two case studies showcase how IoT-based condition monitoring solutions help injection molding operators solve production issues while increasing safety, productivity, and quality.

 

Injection molding for the medical device industry

The challenge

A large injection molding company that produces components for the medical device industry struggled with maintaining the quality of a particular molded part. Production runs were inconsistent due to temperature and pressure anomalies in the mold injection lines, which resulted in a short shot, or incompletely formed parts. This caused production downtime, as well as increased part inspections and scrap.

The solution

Accurate and continuous monitoring of the temperature and pressure lines with SensoNODE™ Sensors and Voice of the Machine™ Software revealed a small leak in a pressure hose that caused the pressure to drop at certain times during the molding process. With the hose replaced, SensoNODE and Voice of the Machine Software ensured the pressure remained stable during the process. In addition, data collection was much easier than utilizing standard gauges, which would be in difficult-to-see locations within the machine.

Customer value

The injection molding company was able to fix the problem quickly, minimizing downtime and scrap. The company also avoided a serious product recall risk that comes from shipping out-of-spec molded parts to a medical device customer.

 

Monitoring pressure for stamping press and injection molding

The challenge

A customer that makes washing machines and dryers had been using manual diagnostic test tools for their manufacturing processes and machines where a majority are hydraulic-based assets. Two pieces of equipment in particular – an injection molding machine and a stamping press – are driven by the same hydraulic power unit (HPU).

Results-Driven Approach to Improve Productivity and Quality in Injection Molding diagram Quick Coupling Division

The HPU is located 20 feet off the floor at the top of the machines. In order to diagnose or evaluate each asset, a maintenance technician must use a manual diagnostic tool connected to the HPU to collect pressure changes at several points of interest. A second technician would be on the floor watching and cycling the machine.

Those technicians would then test several points individually, which took hours. Because the manual diagnostic devices have long cords that connect the sensors to the handheld meters, the set up for testing was cumbersome and time-consuming. Technicians would shut down the machine due to safety risks, then set up the tools to take readings, which further extended downtime and led to missed revenue opportunities.  

The solution

The customer needed a solution that allowed a single maintenance technician to test multiple functions simultaneously as well as take readings from the floor while also observing asset processes.

By installing SensoNODE Sensors at each of the five points of interest, the technician is now able to run the machine and use Voice of the Machine Software to track all pressure measurements at once, as well as watch the machine functions from a safe area.

Customer value

Being able to monitor multiple points at the same time simplifies the troubleshooting of a complex system, which helps technicians quickly resolve issues that minimize downtime and saves money. In turn, the injection molding manufacturer’s customers receive quality products on time leading to increased satisfaction and loyalty.

 

Learn more about our injection molding solutions or speak to an engineer to discuss your injection molding issues.

 

Results-Driven Approach to Improve Productivity and Quality in Injection Molding Dan DavisContributed by Dan Davis, product sales manager, SensoNODE Sensors and Voice of the Machine Software, Parker Hannifin.

 

 

 

 

Condition Monitoring in Injection Molding

Condition Monitoring for Today’s Metal Fab Industry

Injection Molding: Monitoring Multiple Points of Pressure

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