Before we dive into the quality issues that arise from manual data entry, let’s review the ways in which data is handled in industrial calibration processes.
Quality managers looking to find real insights from pages upon pages of raw quality data might not be successful. But managers with Statistical Process Control (SPC) software will have a leg up.
The Internet of Things (IoT) is the new standard in manufacturing today, deeply affecting the way manufacturers operate. Improving Overall Equipment Effectiveness (OEE) is crucial to IoT. Optimizing OEE requires accurate, up-to-date data across an entire organization, including measurement and test information from both quality labs and the shop floor.
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.
SPC can go a long way in reducing variation, but organizations may avoid roadblocks.
May 6, 2021
In order to remain competitive in today’s global economy, manufacturing companies are working to improve efficiency, productivity and quality. To do so, they must proactively prevent defects instead of corrective action.
The L.S. Starrett Co. announced the introduction of DataSure® 4.0, an advanced wireless data collection system for acquiring precision measurement data. With unprecedented range and data security, multiple gateways, compact size and high speed, Starrett, a forerunner in the development of data collection solutions for quality control manufacturing applications, claims the system has taken data acquisition to a new level.
Inspection reports are an invaluable part of the manufacturing process in many industries, and first article inspections are especially common in aerospace, defense, automotive and medical devices. In other words, if high quality is essential, these reports often are too.
I’m a Type-A personality with a sense of urgency to explain everything. Give me a little data, and I will use every statistical tool I can wrap around these rationalizations to help explain an observation. But here is something that I cannot explain: why do we tolerate such poor gages?
To drive change in any business process you must first assess your existing program. Is it inclusive? Is the program delivering results? How can it be improved and how can success be measured?
Our industry is fraught with tales of quality audits from hell and other less than desirable places, usually the result of standards written by folks who know a little but expand it to encompass a lot.