The topic of quality is an important one to all industries. From the healthcare industry to manufacturing, quality improvement is always at the forefront. Quality Improvement Definition sometimes can vary because of how broad the concept is and how broadly spreads. But regardless of the definitions, the idea of quality and quality improvement are rooted in certain fundamentals that do not change. Let’s discuss some of those fundamentals below.
The Fundamentals of Quality Improvement
Independence and control
In order to maintain quality, there has to be a balanced level of independence and control. For example, in manufacturing, you can’t have to same level of control for every manufacturing process, especially for really large manufacturing plants with tons of different stages and process. Same way you can’t be lenient in all processes as there are some processes that are more important than the rest. It is important to have a contract manufacturer provides you with required information so that you can close this gap of lack of knowledge and experience with your products. Despite this, it is essential for organizations to you establish an independent and unbiased quality in manufacturing monitoring system. This is critical! Management cannot always rely on receiving important and complete information that would help quality improvement initiatives if they don’t put effort and are proactive about it.
Test the production process
In order to maintain quality, you have to place checkpoints throughout the production process. These checkpoints will serve as test checkpoints to check the flow or quality from one stage to the next. Each discrete stage of the production flow should be tested before your product can move on to the next. Ideally, you should deploy test stations (manual or automatic) throughout the production process. In manufacturing, for example, testing should start with the inspection of incoming raw material, right through to the final stage prior to the delivery of final goods to your clients.
Analyzing the Testing Data
Most things need to be analyzed and tested before they are considered ready to use. Same goes for a quality control process. Analyzing the testing data stored in all testing station located on your manufacturing line is very important. This data provides invaluable information. It allows us to conduct root cause analysis of quality issues, and over time improve production quality.
In order to maintain quality, manufacturers need to maintain a time frame. Production downtime is a nightmare for manufacturers. It may lead to significant delivery delays for your customers and damage the quality of your goods or of your process. Only proper production monitoring system will help in minimizing this risk. It is essential that manufacturing managers have a direct and quick access to the data collected from the testing stations which are located on the manufacturing line. When there is an issue, they need to be able to react rapidly. Run root cause analysis. Identify and fix the problem, and resume full production as soon as possible. This will help maintain the quality of the manufacturing process.
Don’t only rely on“Pass” or “Fail”
In the technical world of manufacturing, usually testing stations located on your manufacturing line (manual as well as automated) measure several technical parameters. The testing concludes with an indication – “Pass” or “Fail”. If the test result shows a “Pass”, then the unit is moved on to the next manufacturing stage. If the test result shows “Fail”, then the unit is sent to a technician for further analysis. Manufacturing managers should also rely on other testing criteria spread across a spectrum as opposed to just relying on pass or fail criteria. This will result in better quality monitoring. The reason is information overload. When running a mass manufacturing line it is impossible to routinely “digest” all the detailed information collected from testing stations. Using just the “pass or fail” ranking gives no detailed insight or information about the quality problems and what could be wrong.
Using a scale on a spectrum is a better system and gives better results. Edge cases may lead to unit failure during operation, for example in extreme environments (cold, heat, humidity, electrical overload, impact etc.). For accurate and useful quality data analysis, you need to find a method that will let us routinely review the entire test data for the unit and analyze it in a meaningful way with other tested units, other testing stations and with historical test data. This will allow a proper production monitoring system that ensures best quality in manufacturing.
Visibility of Process
There should be visibility of the whole quality in the manufacturing process. The manufacturing process is a chain of separate but dependent assembly and testing processes, which together build a final product. Or in the case of the healthcare industry, it is an entire chain of staff of different levels and departments that come together to provide the final service which is care and the goal is to have a higher quality of care. Another example is that a technical problem created in one stage of the manufacturing process may only be identified in later test stage of production process. For example, a defective button assembled on a unit may only be found during functional testing, several stages later. In order to see the entire picture quality maintenance managers need to collect and analyze the end to end results according to the severity and the frequency of each problem found.
Lastly having an alert system in your manufacturing process helps to maintain quality. Being Alerted when something goes wrong. The manufacturing of your products may be taking place on another continent. It may be taking place in the next room. Either way, you need to be alerted so that even if you aren’t there to keep a close eye on each stage in the quality in the manufacturing process, you will still be aware of major problems the instant they happen. An automated alert mechanism that generates notifications about critical problems on the production line is an absolute must for production quality monitoring.