Quality 4.0 must be a significant contributor to the Industry 4.0 revolution happening in manufacturing, however, right now there is a significant gap between the two. The risk for the quality industry not closing, or at least not tightening the gap, will have a negative impact on the entire manufacturing industry. There are multiple reasons for this, particularly for high production runs, complex parts, and parts in industries that are heavily regulated. In addition to hampering innovation, it also stifles the quality department and functions as a whole, keeping the quality reputation as the ‘go/no-go’ department in any given manufacturing organization.
This technology gap between quality and other aspects of the manufacturing process has steadily grown over the years. Some of the lagging has to do with the technology itself, and some of the responsibility involves business owners and managers who do not view expanding the quality function as a critical business need. Further, some of the chasms have been built from ‘in the box’ thinking that quality is only defined as a ‘good or bad part’ and not how the quality function can broaden its scope, synchronize with plant operations, and support the manufacturing industry as a whole with error prevention and even supply chain improvements.
There are hundreds of different inspection tool types, tens of thousands of measurement tools, from manual to Bluetooth, wireless, CMM, vision, arms, laser—the list is long and growing daily. The biggest issue is not about measuring the part correctly but how the measurements are recorded, where the inspected data resides, and what real value that data provides beyond ‘good or bad.’ In most cases inspection results are written on a piece of paper then typed into a spreadsheet, or captured by Bluetooth/wireless/wired devices, or as printed results from a CMM, vision, arm or any of the myriad other inspection tools we use for measuring the average part from start to finish.
One quality executive said to us recently: “I have millions of inspection data points daily, but I do not have any information that will help me make a decision for quality improvements in the manufacturing process. Inspection results are spread all over the place, collected manually, or by different software programs. In the best case, the data is stored in folders. In the worst case it’s just papers in a box, and as my department is always behind, there is no time to think about changes or improvements.”
The Roots of Quality
What are the root causes for this gap and more critically, why is it growing? One cause is that every new product starts with an idea, preliminary design, prototyping, testing, costing, and then quoting from the supply chain. In most cases quality isn’t considered in these upfront activities as a contributor but just as an enforced cost near the end of the process before shipping. Other causes include the complexity of parts, higher volumes to be inspected, frequent new quality regulations, transparency to OEMs as required, statistical process control (SPC) data, and much more. On top of all the above, there is continuous pressure on decision makers to shorten delivery time, cut costs, and beat the competition domestically and worldwide. Adding more fuel to the fire of an already burdened quality function, now some OEMs provide only 3D models with product manufacturing information (PMI). This new approach, with minimal information about the part to the supplier, is known as model based definition (MBD), model based inspection (MBI) or model based manufacturing (MDM). This relatively new OEM strategy puts more on the quality function rather than less. With models versus a 2D print, quality technicians have to ‘dig out’ the missing information that they need to know for the multiple steps they need to do.
Meanwhile, traditional methods of obtaining quality specifications from 2D part prints is grossly inefficient. Today, more than 75% of the industry still uses a pen or pencil to ‘balloon’ part prints manually. Quality requirements are manually extracted and interpreted, and then entered manually into a spreadsheet with many of the other related quality steps. Each action gives an opportunity to introduce errors to the process. This first step, among many to follow to the quality processes, creates a huge burden, liability, and workload to the quality process, and definitely answers the question about why the quality industry is farther behind other gains in manufacturing.
Delta Corp. is one example of a company using the new automated quality system. Bob Sakuta, president and managing partner, said, “I always told my customers that I can control and compromise only with two of the three slopes on the triangle: cost, delivery, and quality. If you can’t compromise on quality and delivery, your cost will be higher. If you can’t compromise on delivery and cost, you will have to give up on quality. This is how the dependency triangle worked until integrating an effective, automated quality management system. Now at Delta, using the new system, there is no need to compromise. We can provide all three.”
Author: Sam Golan – Founder & CEO HIGH QA
For more information: www.highqa.com