Intelligent Software and Data Drive Continuous Improvements with Ease and Speed

Today, manufacturing companies are challenged with balancing increasingly complex operations with outdated systems. However, the companies that prioritize innovation and adopt modern technology benefit from intelligence that can reduce the complexity – or provide greater insight into it – helping them be more agile and responsive. This type of transformation not only allows them to innovate continuously but can catapult them ahead of their competitors.  

Traditional Methods of Addressing Process Improvements 

The traditional product assembly line works as follows: materials that make up the end-product go through an assembly line, where a mix of operators at stations and machines (i.e., robotic systems) assemble the materials to create the product. The product is then tested – if it fails the test, it’s a defective product that becomes scrap material, and if it passes, the product goes to the customer.

In an ideal world, assembly lines would have no downtime – meaning, every line is running perfectly, with no issues or delays and at 100% overall equipment effectiveness (OEE). In the real world, however, 100% OEE isn’t realistic. 

Three factors that often contribute to reduced OEE are availability, performance, and quality loss: 

• Availability loss: occurs when there isn’t enough of every material needed to create the product, so production pauses until those materials are available. To combat this, teams often manually review data and create a specified material replenishment schedule. Equipment failure can also shut a line down. When this happens, engineering teams must respond in real-time and shut down operations until the issue is fixed; to prevent this, these teams manually review data from siloed systems and set a preventive maintenance schedule to reduce downtime.

• Performance loss: can happen when the line has sub-optimal performance and is not producing as many units per hour as it could be. For example, performance loss can occur when the line operator doesn’t have the correct skill set and is performing at a slower pace. To track this, manufacturing companies often have sensors, clocks, and cameras to gather data on each line, and then the team does a manual analysis to determine where operator bottlenecks are occurring. 

• Quality loss: this is typically discovered during the final testing phase. For example, a company does ten tests on the product in 10 minutes, but the team wants to eliminate redundant testing to get the time down to 5 minutes – this requires manual analysis to determine where they can make changes within the testing phase while maintaining the same quality levels. 

Manual data collection from spreadsheets, notebooks, and stopwatches to determine where process improvements can be made on an assembly line is often time-consuming and error-prone and takes resources away from other important initiatives. While there will always be assembly line challenges, there are now ways to address them faster and smarter with the latest advances in technology. 

Modernized Process Improvement with Brightware® Insights

??Brightware^® Insights is a software application that delivers analytics and data visualizations to enable manufacturing process improvements to Bright Machines Microfactories. It complements  Brightware Studio by identifying correlations and trends, leveraging historical data.

Using a cloud-based application architecture, Brightware Insights provides standardized data modeling and visualization templates tailored to a range of users. In other words, different roles within the manufacturing plant have access to the same data but have different views or perspectives of it that are unique to their role and responsibilities. 

A process engineer, for example, could start to analyze potential bottlenecks on a microfactory line via Brightware Insights dashboards that have relevant information such as cycle time statistics. They can see how many cycles ran and the average run rate across all lines. With this level of detail, the process engineer can run additional tests to determine where adjustments can be made to increase cycle times.  

A line manager who wants to ensure consistent quality on the line can set up a rule that says, if the yield drops below 98%, they need to receive a pop-up message, text, or email notification. Once they’re informed, they can then look at data visualizations that show the yield over time. For example, they can see where the yield was over 98% and at which point it dropped below. By having this historical view, the line manager can understand when and where the issue occurred and take the appropriate steps to address it. 

 Data-driven intelligence enables three key improvements: 

• Faster response to equipment issues: Maintenance engineers can more easily and quickly identify the root cause of equipment issues by leveraging diagnostic tools within the application, allowing them to respond to problems quickly. 

• Improved cycle times: Process and automation engineers have access to dashboards to see which potential problem areas to focus on and where the bottlenecks could occur, which can improve and reduce cycle times if prevented. 

• Lower defect rates: Line managers and quality engineers can ensure that they’re notified if yield drops below its set target rate; they can then assess the data and understand what’s causing the failure and how to fix it to eliminate end-product quality issues.

The Brightware Insights application makes it possible to access meaningful decision-making data directly, not only for engineers on the factory floor but also for the managers responsible for automation projects across locations – ultimately resulting in faster response to equipment issues, improved cycle times, and lower defect rates. 

Ready for Action, From Day One

Each Brightware application offers additional functionality on top of the Bright Machines^® Microfactory, a process standardization solution for assembly automation. The microfactory and Brightware Insights are integrated from day one. Users can log in to their accounts and pull data that will provide actionable insights without doing the integration work themselves. 

At Bright Machines, our vision is to rethink manufacturing. Brightware Insights builds on this vision by enabling analysis of historical data across multiple Bright Machines Microfactory lines and production sites to facilitate/speed insights for optimizing production efficiency, improving quality, and increasing equipment uptime. The application also extends our full-stack approach with enhanced functionality that equips manufacturers to understand their operations better and enable faster process improvements.