AI Use Cases for Manufacturing Vertical

AI Use Cases for Manufacturing Vertical

Lots of news and talk about AI Usecases in Technology, retail consumer, and health care verticals.?I feel we need more focus on the manufacturing vertical which can get enormous benefits from this exciting new technology.?

After a large amount of shifting manufacturing to low cost countries, now rich/developed countries are moving factories back into their home country due to voter’s concerns about job losses.?However, the same voters are not willing to pay higher prices for their goods and services.?Hence the focus is on the use of AI technologies to the fullest to manage the jobs and cost conundrum.

Andrew NG, AI Guru, is focusing on the effective deployment of this new technology in enterprises.?He is promoting Domain Specific Visual Models targeting manufacturing, electronics, food & beverages verticals.?

We at @AiThoughts.Org agree with Landing.Ai approach and started advocating the use of Vision solutions to solve many problems in the manufacturing vertical. ?We debated with our manufacturing experts and identified a sample e of a few use cases worth consideration.

1.??????Quality control of incoming supplier materials at the receiving dock or even at the shipping dock at the supplier’s premises. ?With the complete ecosystem in the manufacturing life cycle at extreme margin pressures, short-cutting of quality of the materials supplied is a real concern and any fast, mostly automated solution will be a great solution.?Bad quality material will eventually make the manufacturer's end product bad and increase customer returns or increase customer complaints. In many cases, this may even disrupt the assembly line process causing unplanned shutdowns costing $$s.

2.??????Quality control of sub-assemblies and final product.?Landing.Ai ’s first product launch for based on this use case.??Customer returns or customer service requests post shipment are huge concerns of any manufacturing company.?Any solution where a large amount of sub-assembly and end products can be quality-checked by AI models will be very useful.?In many cases, this may not be a human replacement solution but human enhanced solution.

3.??????With factories becoming more automated with conveyor belts, and human-Robot workflow assemblies, employee safety in factory premises becomes a major concern.?AI visual solutions to ensure humans are safe at all times, provide ample warnings to humans to stay away from risk areas, and even shut down systems such as conveyor belts, robot assembly, etc. to save a human worker from harm are needed.

4.??????I can go on with other solutions as I am very passionate about Manufacturing and spent first 15 years of my IT career helping customers in the Manufacturing verticals.

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As a bonus, there are problems in the global supply chain that still need to be solved using AI.?The optimization of JIT vs safe inventory both for raw materials and finished products is a long-standing problem. ?Even large enterprise software providers have not found any new solutions or new algorithms to attack this problem. The industry needs a holistic AI-based solution taking into consideration the end-to-end life cycle from supplier production, global shipping, port loading/unloading workflows, road transportation, quality rejections, own factory scheduled maintenance, customer orders and a host of other employee union/strike-related issues at supplier side and own side …?The problem is very complex and needs a good AI solution.

Hoping that this post will create more interest in the manufacturing vertical amongst the T community and that some solutions will come along.? AiThoughts.Org is available for any help in this regard.

More later.?

L Ravichandran