Big data has been a popular topic in the industry already for a long time, but in reality only a small part of data collected is utilized – only approximately 5% of data collected in organizations on average is efficiently utilized. However, from the perspective of quality management, data involves a huge amount of valuable information.
Most typically, problems faced with data utilization are related to poor traceability (what has been done, at which quality level, by whom and when?), data fragmentation and a patchwork quilt of systems, user roles in data collection and defective metrics and targets.
When we want to develop quality, the first step is to examine the upstream part of the chain: data collection methods. What are the critical points in terms of quality and how should quality be measured at these points?
Three quality management tools – how is quality data created?
There are three generally suitable solutions available for quality management in the industry. These quality testing methods produce valuable raw data, comprehensively from the production process, which is useful, for example, for identifying root causes and for product development.
1. Sensors and measuring systems
Many people are certainly already familiar with various sensors and measuring systems. Sensors are used to collect information about products, processes and operating conditions with continuous time series analyses, process measurements, etc. For example, this could mean a building automation system, a circumstance monitoring system, condition monitoring measurements, or measurement systems connected to production machines and processes.
2. Digitalization of manual testing
Manual testing is still frequently used in the industry: manual inspections, measurements and tests, for which the results are recorded in Excel worksheets or on paper forms. By digitalizing manual testing, significant benefits can be achieved with relatively moderate actions. However, the solutions selected must suit the workflow and support the work steps rather than increase the number of recordings.
For example, digital terminals placed in a production line can control and improve the performance of the operator or the tester. At the same time, the number of errors is reduced and the data collection model becomes standardized. Digitalization also enables data enrichment by connecting valuable metadata to it, which will help analyze data at a later stage.
3. Automated testing
Automated testing is the cornerstone of modern quality assurance. It becomes actual when larger volumes are processed and testing becomes too cumbersome, test requirements increase or the test process gets so complicated that it cannot be performed manually. Automated testing can be carried out at individual test points or in larger test environments either fully automatically or with semi-automatic testers.
Automated testing minimizes errors and variations due to the user; however, at the same time, it is important to recognize quality variations caused by the environment or product batches, for example. Self-diagnostics and wearing of testers can also affect the test results.
A management platform for quality and traceability data makes data real-time and transparent
To draw conclusions essential for quality based on the data collected and thereby genuinely gain a competitive advantage – in the form of customer satisfaction and cost effectiveness, for example – it is necessary to understand what quality is made up of as a whole. An overview can be created by analyzing the production process and identifying essential items for quality and traceability, such as components, work steps, monitoring requirements and reporting needs.
Hence, individual or independent pieces of measuring or test equipment do not solve all challenges related to quality management. Different processes and complex production chains of manufacturing plants cause fragmentation of data, where individual challenges rising because of them are often tackled with various partial solutions. But what if the solution for the entire quality management palette, from the shop-floor level to management reporting, would be more efficient and comprehensive using one single technological platform?
With a scalable management platform for quality and traceability data, real-time quality data can be harnessed to provide a shared decision making tool for the entire organization. For example, the Sight by Pinja equipment and software platform offers a cost-effective and easy-to-use tool for quality leadership. Careful and centralized data management enables, for instance, real-time monitoring of production conditions and quality traceability to individual product batches allowing prompt product recalls and warranty repair services.
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Measurement, testing and quality assurance
