A Dive Under the Hood
In our last post, we tackled the topic of why, despite being around for some time and having tremendous potential to revive the industrial sector, AI robots haven’t caught on in manufacturing.
This is no budding technology: sectors such as logistics, security, cleaning, and agriculture adopted AI robots, with corona virus acting as a major boost. Industry it seems is the only one lagging behind
We offered reasons: massive investments that inflate CAPEX; long decision-making cycles; cultural gaps between young robotics companies and traditional industrialists; wariness of expensive machinery that may turn obsolete even as you are paying for it; and disruption to production.
In this post we touch on how an employment agency for robots solves these challenges, with an ‘under the hood’ look at the Industrial Robots as a Service (IRaaS) business model, and introduce four ways it overcomes the obstacles in deploying a robotic workforce.
1. Choose the leasing model most profitable to you
For an operations or factory manager, we think the most striking benefit of IRaaS by far is the ability to choose the payment model to maximize the profits. A few examples:
Example 1: A robotic quality control visual inspector for Jet engine composite fan blades. Jet engine blades are sophisticated labor-intensive industrial products with unit prices standing at (gasp) around $30 million. Non-conformity is a major issue (cost plus safety). A quality inspection robot would save considerable labor costs and improve quality. Since an average factory manufactures only hundreds to thousands of blades per year, the best leasing model would be a pay-per-use unit (payment per blade the robot inspects).
Example 2: A robotic quality control visual inspector for spur gears
Spur gears, on the other hand, are simple industrial products manufactured with relatively little labor. Machines cast and cut the gears, and humans usually conduct visual inspection throughout the process.
Here, quality control issues may not be as fatal as in a jet engine fan blade, but non-conformity could still be dangerous and costly to the manufacturer. Moreover, factories producing transmission gears are facing a shortage of workers willing to do such monotonous work.
Since a factory can spew thousands, sometimes tens of thousands of gears per day, the best leasing model for visual inspection robots could be a yearly subscription.
Example 3: An autonomous mobile forklift robot for a tea manufacturing plant. Here the autonomous mobile forklift robots can transport raw materials and finished products efficiently and on-demand, can save considerable labor costs and increase safety on the production floor.
This particular factory has a wide perimeter. The route from the warehouse to the production floor is long and the forklift is utilized only about 15 times per day. In this case the best leasing model could be pay-per-use (paying for each time the forklift is used).
Example 4: An e-commerce logistics warehouse. This warehouse has a small perimeter but requires hundreds (and sometimes thousands) of forklift movements per day. Routes are not fixed and forklift work volumes fluctuate seasonally. On the other hand, the forklifts do not drive long distances, so the best leasing model for this warehouse could be pay-per-mileage(paying for each mile the forklifts drive). The pay per use model allows factory and logistics managers to utilize a robotic workforce to the fullest while ensuring a flexible payment model: paying for parts inspected, hours used, driving distance; and even a flat rate if required.
2. Lease the robots only when you need them
With IRaaS, you can rent additional robots during peak seasons, and “lay them off” when times are slow — another critical saving point, especially for logistics centers who experience a high seasonality or volatility in operations. Robotic forklifts are normally also sector agnostic, so the same forklift robot can be used in different types of factories, making it even easier to redeploy the robotic workforce at a different employer.
3. Plan for a Force Majeure
Coronavirus-induced labor shortages, lower demand and supply chain problems have recently brought production to a halt in many sectors. Manufacturers are reeling from lost income, compounded by capital investments that weigh on their balance sheets.
Traditional industry always viewed the threat of a force majeure disruption as a significant risk — even before Coronavirus — and it is one of the reasons investment in robots has stalled.
Robot as a Service enables factories to avoid the financial burden of high capital expenditures and with it a large part of the risk and the associated costs (risk costs a lot of money). It also lowers dependency on low-level workers, which even during normal times are hard to employ and retain.
Fewer orders? We will lease fewer robots. Do workers have to stay at home? They can work from home because robots do onsite work.
The RaaS model can also contribute to a much more resilient supply chain in times of Force Majeure because it can maintain production levels and provide greater flexibly in adjusting to business fluctuations in times of uncertainty.
4. No disruption to production flow
We at MusashiAI come from manufacturing, have worked in the industry for years and understand the disruption that even the smallest change can make to the factory floor. That is why we begin each initiative from the view point of zero friction. Our motto is that new inventions should conform to the production line, not the way around.
We know the biggest impediments to innovation are fear of failure and high costs. Production engineers have no room for either:they are measured not by innovation but by through put and quality.
The robot employment agency concept was born out of this world view: no friction, low costs, and low risk of failure. Even when you do fail the costs are negligible so you can continue with little damage to the factory and to your reputation.
We believe our Forklift and Visual Quality Control Inspection robots supplied in a robot employment agency model are game-changers, and that once production engineers and managers learn about them they will sit up and take notice.
Tune in to our next post that dives into our autonomous mobile forklift robots and Visual Quality Control Inspection robots and the innovation they embody.
Maestro @ 634.AI - Any Thing From Here To There
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