Made in the USA
After decades of watching manufacturing move offshore, Atollogy’s Digital Industrial Engineer provides another option
As global competition drives prices down and escalating labor rates drive costs up, US manufacturers struggle as they watch margins consistently erode. Over the past two decades, US companies considered two options to move toward profitability: automation or outsourcing.
Automation is a viable option for some. These companies have capital available for investment, have processes that are repeatable enough to automate, and most importantly have technical support staff to ensure that the complex machinery is consistently operational. Even with the perfect environment, a slow production ramp-up can wipe out planned gains.
Other companies choose the second option, outsourcing production to third parties, often off-shore. This generally results in a drop in product cost but is offset by increased transportation cost and the additional inefficiencies of a multi-company global supply chain. Even if initially successful, the miles and time zones between the development and manufacturing teams slowly erode the design for manufacturability approach and limits cost reduction through improved manufacturing efficiency.
Atollogy launched in 2016 with a goal of revolutionizing how physical operations are managed and to give companies a new option to improve operational performance. After years in consulting and seeing the issues created by slow automation introductions and global outsourcing, Atollogy’s founders realized that providing better insight into existing production inefficiency could broaden the portfolio of possible solutions. In many cases, the theoretical capacity of the production system exceeded the needs of the company, but with Overall Equipment Effectiveness (OEE) consistently below 70%, organizations can struggle to achieve cost targets.
Atollogy’s Digital Industrial Engineer (DigIE) brings perfect vision to manufacturing operations! Taking advantage of camera technology and tapping into the exploding capabilities provided by AI and machine learning, DigIE replaces the manual and tedious Industrial Engineering tasks of data collection and data processing. DigIE rapidly provides customers with insightful information on how to improve business processes. With a monitoring & analytics solution that is unbiased, never sleeps and never forgets, our customers are able to rapidly digitize what is often a “silent” operation and within a matter of weeks make changes that start reducing unproductive time.
Often, a key initial observation is that operators really “want” to do a good job. US production operators have developed a bad reputation, but in many cases, they are as frustrated as management with the inability to consistently produce parts and products. DigIE instantly becomes one of their best friends by quickly identifying the activities that are keeping them from producing parts. Maybe they are pulled from the station to retrieve material or build packing boxes. Possibly a delayed response from maintenance when the machine goes down or a quick maintenance response, but the wrong skill set to get the machine operational is contributing to unproductive time. The entire mindset of the workspace changes when a supervisor can congratulate a production team for exceeding expectations during “productive” time and the entire team is working together to minimize “unproductive time”.
Although DigIE provides detailed information, it currently does not make business process change decisions (stay tuned for a future blog on leveraging AI for dynamic process change). Now armed with detailed insight into operational issues, companies are able to increase productivity without making dramatic automation or outsourcing decisions. Two common approaches are headcount balancing and the introduction of automation for operator assist.
A detailed understanding of operational bottlenecks and the activities keeping operators from consistently staffing these critical operations allow companies to adjust staffing plans to ensure continuous operation. A good example of this is adding a floating operator responsible for assisting with trimming and packaging activities to support multiple operators running injection molding machines. Machines are no longer idled while the primary operator is performing secondary tasks.
Operator assist automation is much cheaper than fully automating a process and can significantly increase throughput. Traditional lift assist or gravity flow conveyors are good examples, but slightly more sophisticated robotics that allow an operator to queue up component material or remove finished product can in some cases allow one operator to take the place of multiple.
Even though Atollogy’s DigIE solution primarily focuses on enabling companies to rapidly increase OEE, it is also capable of detailed process analysis enabling the improved theoretical performance of the operational bottleneck and an uplift in potential output. With the ability to provide both quick uplift and long term continuous improvement, Atollogy hopes to reverse the trend of manufacturing outsourcing and drive a resurgence in “Made in the USA”!
Happy New Decade from the Atollogy Team//php comments_template(); ?>