Posted by Zeeshan Zia, PhD
I was just counting our internal travel logs, and it turns out that over the past year and a half, right in the midst of COVID, our team has somehow been able to visit slightly more than a hundred factories. Many of them multiple times.
Several of these visits were arranged by our friends at the Center for Advanced Manufacturing in Puget Sound (CAMPS), Techstars, Plug and Play Detroit, and Unknown Workforce Technologies. Some were customer exploration opportunities, others, preparations for actual deployments.
Obviously we wanted to maintain a record of what we were learning from these visits, and we spent a lot of time discussing various formats and dimensions along which to quickly assess and summarize what we were seeing. The most valuable insights came from David Crawley, currently CEO of Ubiquity Robotics, who has spent more than a decade visiting factories and running such assessments from his career at McKinsey. Today we share those five dimensions along which we analyze a factory for its organization. You will undoubtedly find relations between our approach and ideas from the Toyota Production system including 5S and the Lean Manufacturing House.
Assess along five dimensions to distinguish between five levels of factory organization
We wanted a quick and clean way of thinking about the floor that will be scalable, and we arrived at the following five dimensions: man, machine, materials, mother nature (environment), and melioration (or continuous improvement).
We define five levels of factory organization that roughly correspond to growth along the lean manufacturing house as follows.
Level 0 factory: A “level 0” factory looks like a badly organized local garage. There is a general disorder, where we see equipment not in a logical place. There are piles of large quantities of inventory found placed at random locations. We see workers operating in a very casual and unstructured way. When we talk to the plant manager or equivalent, it becomes immediately clear that there is no formal or informal process improvement plan in place. We roughly see 10% of factories as falling in this category.
Level 1 factory: A level 1 operation already looks significantly more standardized than a level 0 operation. All equipment is structured in a logical sequence, but not necessarily marked. We find large quantities of inventory placed at standardized locations. We can clearly see workers operating with a sense of purpose. We find that process improvement happens occasionally in a strict top-down manner, directed by the plant manager. We put approximately half of the factories we visit in this category.
Level 2 factory: We define a level 2 factory as one where there is a clear workflow for the equipment. You step on the factory floor and it’s clear what’s going on. Work is standardized. There is not a lot of inventory lying around everywhere. Workers seem over run with work. There is lighting in key locations, and the floor may be immaculate. Quality circles are regularly organized where groups of workers who do similar tasks meet to identify, analyze and solve work-related problems. We find that less than a quarter of factories in the US fall in this category.
Level 3 factory: A level 3 operation is ordered, tidy, and the steps are clear even on a first glance to an outsider. There are clearly market inventory locations, but there is very little inventory there. Everyone is busy but not rushed. It’s obvious that the organization has an active 5S program, e.g. its clear they are tidying up daily. There is an energetic and active improvement program in which everyone is involved. We classify around 17% of factory floors we visit to fall into this bucket.
Level 4 factory: We have visited only three factories that completely fall in Level 4, and one which satisfies our criteria for Level 4 along 3 or 4 out of 5 dimensions. In these operations, it is impossible for the product not to go in the right place. The placement of equipment has gone through multiple rounds of optimization. You don’t see any inventory that isn’t being conveyed or worked on. The workers look like the interior of a swiss watch or like a military marching band. They will be operating with a rhythmic motion. There is no more lighting or cleanliness than is strictly necessary. There is a professionally led improvement program that is fully driven by worker input. Obviously, we were intrigued when we saw such operations and tried to learn more from plant leadership and workers. Across all three of these factories, we learnt that it took them decades of discipline, continuous improvement, transfer of knowledge from their sister factories and training in lean manufacturing to get where they are today!
Relation with the Lean Manufacturing House
If you have read this far, you must be seeing parallels to the Lean Manufacturing House, which is a more comprehensive analysis and improvement framework. Our objective here was to assess a factory floor within seconds and minutes, whereas workshopping growth along the lean manufacturing house is an activity that requires days and weeks.
Here we want to briefly point out some of these parallels. Our “level 1 factory” roughly corresponds to just the foundation of the lean manufacturing house. When applied to a production system, this refers to team stability, standardized work methods, continuously monitored strategy, etc. A Level 2 factory corresponds to the base of the lean manufacturing house, where Kaizen and reduction of MUDA are high priorities. The third level roughly indicates the two pillars of the house namely, JIT and JIDOKA, and so on.
Who do we work with?
So why do we assess factories along these dimensions? We find that the ideal customer for our RetroActivity platform lies between Level 2 and 3. Our objective is to accelerate their journey towards a Level 4 factory. In the lean manufacturing house, you will notice that our solutions correspond to the pillars of JIT and JIDOKA. At the same time, we find that in several verticals such as automotive, several Level 4 factories are in danger of slipping down this hierarchy. This is because changes in customer demands are forcing these factories to change processes and introduce new ones at an unprecedented pace. We are deploying with at least one such factory and hope to continue growing our Level 4 customer base.
We don’t work with Level 0 and 1 factories. We find that such factories are able to capture the largest gains from non-technological initiatives, such as better lean manufacturing education.
References:
The Lean Manufacturing House (link)
Brandin and his team help our customers with setting up the Pathfinder platform and getting up-to-speed on all the features and functionalities, in addition to assisting them with standardizing their processes where needed.
Brandin is a seasoned manufacturing leader, who has spent more than a decade designing and setting up assembly lines in both the US and China, optimizing them, and working with human operators to maximize productivity and quality.
Huy takes our product roadmap and figures out what’s achievable with today’s AI advances, and what we need to invent to solve our customers’ pain points.
Huy led teams of scientists and engineers at NEC and invented technologies for driver assistance systems that are part of 500,000+ Honda cars. He is an inventor on more than 20 US patents, and his research papers are cited by every lab from MIT, Stanford, and CMU to Apple, Google, and Baidu.
Jesse works closely with our marquis customers to understand their needs, and figures out the best solution that immediately adds dollars to their bottom line.
Jesse has two decades of enterprise sales experience. He has held sales leadership roles at pioneering technology startups.
Andrey takes inventions and converts them into innovations. He leads our product engineering team to turn our scientific prototypes into robust customer-facing products.
Andrey co-founded and successfully exited a startup to immigrate to the US. He spent his next eight years building the core data science infrastructure for Amazon’s supply chain planning team, and the CV/ML infrastructure for Microsoft’s HoloLens organization.
Zeeshan focuses on delighting our customers by understanding their needs and defining product and strategy to meet and exceed these needs. He works closely with our sales leadership to grow our customer base.
Zeeshan was a scientific leader at Microsoft’s HoloLens division, where he invented AI technologies to assist frontline workers across industries. Earlier, he shipped IoT platforms and visual defect detection software for manufacturers at Siemens and MVTec GmbH.
