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Jun 9, 2022 | Time to read: 4 min
Mature organizations seek to streamline their practices and ensure that people are able to focus on the work that is important to their role. The line worker shouldn’t have to worry about how the material is arriving at their station or how the product will be shipped (unless it is part of the scope of their responsibility). That said, the people responsible for specific portions of the work need to be at the center of authoring the processes. Too often, for example, a design team is made responsible for creating the assembly instructions for a process (when they are not the ones who will do the assembling). While this is fine during prototyping, the best standardized work instructions and systems are led by, and get feedback from, the people doing the work. Ultimately, the worker determines whether or not a standardized work process is effective.
“Every team member has the responsibility to stop the line every time they see something that is out of standard. That's how we put the responsibility for quality in the hands of our team members.” ― Jeffrey K. Liker (source)
In fact, one of the most important steps a manufacturer can take to improve its processes is to ensure that standardized work is properly implemented in a systematic manner. Standardized work is a foundation on which the rest of an organization's processes can be built, and is the baseline required for effective problem solving. Every organization will have problems, no matter how mature, and it is the systems in place that will determine how difficult it is to identify and solve these problems.
Drishti is built on standardized work, too
Drishti has built a new AI-powered way to digitally conduct constant time and motion studies, create massive volumes of data from the assembly process and use that information to drive actionable insights toward continuous improvement. Here’s how it works:
Drishti installs cameras on desired workstations and streams video of your assembly processes. By the way, you can access this live video anywhere you have an internet connection.
Drishti’s proprietary neural networks work in conjunction with our team of engineers to annotate and recognize key points in the process (as in the standardized work sequence of steps).
Drishti data is used to automatically monitor the process in real time, or after the fact if preferred. Our system can flag long and short cycles, and even notify the worker of step deviations in real time. We refer to this as action recognition (it’s like object recognition, but uses video streams instead of still images).
Drishti automatically shares insights about cycles and individual actions with key stakeholders, including at the line, team, plant and executive level. These teams use this information to quickly identify improvement areas, increase productivity, reduce defect rates, conduct training and more.
Standardized work remains a key part of any lean manufacturing methodology. Even with increased automation, 72% of all assembly tasks are still done by hand. The next wave of technology needs to empower workers rather than attempt to replace them. This is what Industry 4.0 forgets.
While humans are the most important asset for manufacturers because they are adaptable to change, they create variability. That’s why technology like Drishti is so key: it reduces that variability while augmenting human workers’ best assets, like cognition and reason.
Drishti does the equivalent of three tedious tasks rolled into one:
Rather than requiring hours from industrial engineers, Drishti can continuously “stand on the line with a clipboard,” recording cycle times. Engineers can focus on deducing the far richer and more voluminous data and recommended insights and making improvements.
Rather than spending days, weeks or months conducting retroactive research into the cause of a defect, Drishti can help quality engineers uncover the cause of an issue in minutes, so quality teams can focus on implementing fixes and putting preventive measures in place.
Drishti provides video evidence of best practices, allowing faster worker training and onboarding as well as on-the-spot training as needed.
Drishti customers have seen massive results, including:
50% lower defect rates on lines with very low escape defect rates (~0.001%), in just three months
15% throughput improvement on already optimized lines
15% lower scrap rates
50% faster training times for new workers
Deterministic root cause analysis in 20 minutes
Ultimately, whether in areas of productivity, quality or training, Drishti promotes a new version of continuous improvement that would not be possible without AI and computer vision technology. In this way, Drishti is taking the benefits of standardized work into Industry 4.0.
For more information on standardized work, how to implement it and how to upgrade it read our eBook.
