Software : Operational Technology : Manufacturing Execution System
Critical Manufacturing MES helps manufacturers to digitalize their operations to compete effectively, and easily adapt to changes in demand, opportunity or requirements, anywhere, at any time.
AQL in Medical Device Manufacturing and the role of MES in its implementation
AQL Defined: ISO 2859-1 establishes AQL (Acceptance Quality Limit), as a sampling-based method for determining quality through inspection of attributes. In simpler terms, AQL is the maximum number of defects allowed in a given lot above which the entire lot would be rejected, or the lowest level of acceptable quality.
An MES application, configured for the medical device industry, allows for the creation of sampling plans, based on risk and for those plans to be enforced either on a time or counter basis. The application supports AQL and allows the definition of measurement tools, along with their calibration status and switches severity automatically which is an advantage for high mix production facilities. It measures both variable and attribute data points based either on time or counter and can be integrated with material logistics to give users a complete view of the quality as materials move across the production line and are converted into the end product.
This month cover story of @TMDmag features our case study from @ultradent.— Critical Manufacturing (@CriticalMfg) March 14, 2022
Read the story to learn how this global dental manufacturing company is taking big steps towards the future of manufacturing.https://t.co/u5IUiXQJMH
Big Data Analytics in Electronics Manufacturing: is MES the key to unlocking its true potential?
In a modern SMT fab, every time a stencil is loaded or a squeegee makes a pass, data is generated. Every time a nozzle picks and places a component, data is generated. Every time a camera records a component or board inspection image, data is generated. The abundance of data in the electronics industry is a result of the long-existing and widespread process automation and proliferation of sensors, gauges, meters and cameras, which capture process metrics, equipment data and quality data.
In SMT and electronics the main challenge isn’t the availability of data, rather the ability to look at the data generated from the process as a whole, making sense of data pertaining to each shop floor transaction, then being able to use this data to generate information from a single point of truth instead of disparate unconnected point solutions and use the generated insight to make decisions which ultimately improve process KPIs, OEE, productivity, yield, compliance and quality.