Manufacturers must ask a lot of their quality data collection systems. Ideally, these systems should not only capture quality data while a product or service is manufactured, assembled and installed, but they should also aid in pre-production preparation. They should enable timely transparency across production sites, even those operating under different languages, regulations and jurisdictions.
When done right, advanced data collection systems can support any quality related data collection and reporting application. When choosing a system, leaders must consider both immediate needs and future growth. In other words: will it scale? And, how do we best utilize it as we expand?
A wireless data collection system should consistently collect and transmit measurement data, regardless of application or location. It should also be able to accommodate changing measurement data collection requirements.
Starting with value
Manufacturers that want to get their data collection up to scale should first look to where the system can provide the most value, not where it’s easiest to slot in new technology. Depending on the type of organization, manufacturers have different places to start.
Small-lot manufacturers, such as machine tool builders, should look at overall equipment effectiveness (OEE). How can data help drive their OEE optimization? Mass-customized manufacturers, on the other hand, should start with high throughput and consistent product quality. High-volume manufacturers should focus on automation and increasing OEE.
Afterward, organizations should then prioritize delivering value locally, with the help of their data collection system, before scaling processes across all of their operations.
It’s important that the data collection be automated. This helps businesses collect large amounts of data that is more accurate than manually collected information. Operators can ensure that automated data are instantly reported and analyzed and presented to stakeholders in real time.
This immediate, detailed feedback helps manufacturers to correct problems as soon as they arise. It also helps leaders more deeply understand their operations and take steps to improve efficiency.
Optimizing OEE with data
Manufacturers should approach their quality control data collection systems as tools to help them boost value. The data they can glean empowers them to identify areas that can be improved. It also helps them put continuous improvement practices in place.
A way to boost value is by optimizing OEE.
Optimizing overall equipment effectiveness essentially helps companies to understand how productive they are, and how productive they have the potential to be. Businesses looking to optimize OEE should consider concepts such as throughput, cycle time, yield, customer fill rates and more, as these metrics enable companies to predict future problems and improve efficiency.
Accurate and well-timed manufacturing data helps manufacturers to make better decisions that will boost OEE and, therefore enhance value. These are important factors to consider when selecting quality control data collection systems.