In today’s competitive manufacturing landscape, ensuring high-quality products is paramount for success. To achieve this, industries are increasingly turning to advanced technologies and techniques to enhance their quality control processes.
This is where predictive analysis comes in. When predictive analysis is implemented throughout the quality control process, manufacturers can anticipate and detect quality issues and any production problems before they arise.
But what makes this so different to traditional quality control methods?
Current quality management is only really useful for identifying flaws and issues after it has been checked, and the checks themselves take time. Further compounding this is the fact that rework doesn’t actually fix the root cause of the quality problem, just the problem itself.
Prevention is better than cure
Predictive analysis leverages historical and real-time data to make informed predictions about future events or outcomes.
When used within the context of quality control, it processes and interprets large volumes of data generated from various stages of the production process, in order to identify historical patterns, improve the manufacturing process and increase product quality.
Predictive analysis revolutionises quality control by applying machine learning and statistical models to data. Through the analysis of vast amounts of data from multiple sources, including sensor readings, production parameters, and historical records, manufacturers can identify patterns, correlations, and anomalies that may impact product quality.
This data-driven approach allows them to take corrective actions in real-time, minimising defects, optimising processes, and reducing waste.
Predictive analysis with FLAGS Software
Combining predictive analysis with quality control can deliver complete control, visibility and traceability across the production line, helping manufacturers make the world’s best products.
Predictive analysis is part of FLAGS Software’s DNA.
By harnessing the power of data in real-time reporting functions, interactive smart dashboards and multiple data inputs, FLAGS Software offers precision, identifying any quality issues across the production line, helping organisations achieve the next level of quality, efficiency, and control.
The benefits of predictive analysis in quality control
Early detection of issues
By continuously monitoring data in real-time, predictive analysis can identify deviations from normal operating conditions. This enables shop floor users to record quality issues identified during manufacturing from issues with machinery to mistakes caused by human error.
By identifying the root cause with FLAGS Software, they have a complete digital history of the product being made. Rules can be added to promote error prevention behaviour as well as providing the option that a product can only continue in the manufacturing process if quality issues are rectified. This reduces the chances of defective products reaching the market.
Optimal resource allocation
Time is money, and when resources are being wasted or laying dormant, it costs.
When there’s a query about an item in production or an issue highlighted during assembly, it’s vital to get the right person on the job quickly. With predictive analysis through FLAGS Software, shop floor workers get notifications in real time, and actions are colour coded in order of priority.
Manufacturers get a clear picture of the overall production process, which helps them organise work more efficiently and ensures all notifications are followed up appropriately. This is because predictive analysis looks at every single area of the process, and determines whether it adds value in the context of time, quality and cost.
Traditional quality control is time and labour intensive – especially when data is manually reviewed and interpreted. Through FLAGS Software, once information is logged, it is interpreted into visual intuitive dashboards that manufacturers can use to make data-driven decisions across the production process.
By identifying and rectifying issues early, they can avoid expensive rework, scrap, and customer returns. Furthermore, optimised resource allocation and improved efficiency contribute to overall cost reduction.
The barriers to predictive analysis in manufacturing
According to PWC’s Digital Factory Transformation Survey 2022, 64% of companies are still at an early stage of their digital transformation journey, and whilst manufacturers strive to build a smart factory, it is not without its challenges.
Implementing predictive analysis in quality control requires significant investment in data collection infrastructure, advanced analytics tools, and skilled personnel.
Further complexity is added for manufacturers with several sites and systems, data integration and interoperability across different systems. Additionally, Manufacturers must also ensure data privacy and security to protect sensitive information.
However, when manufacturers work with a quality management software supplier that has extensive experience in unifying sites and systems, the disruption of bringing together business and operations data is eliminated, and all the information the team needs is in one place, with quality at the heart of it.
Smart quality control with FLAGS Software
Predictive analysis is transforming quality control in manufacturing by enabling proactive measures, data-driven decision-making, and improved product quality.
With the ability to anticipate quality issues before they occur, manufacturers can reduce defects, enhance customer satisfaction, optimise resource allocation, and reduce costs.
While implementation challenges exist, the benefits of predictive analysis make it a worthwhile investment for any manufacturing organisation looking to stay ahead in today’s competitive market.
By embracing predictive analysis, manufacturers can unlock new levels of efficiency, quality, and profitability.