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My sense is that robots are in use more than the article makes out. Anywhere there is a risk of human error or repetitive work that can be simplified, you'll fi
by donalhunt 5y ago
My sense is that robots are in use more than the article makes out. Anywhere there is a risk of human error or repetitive work that can be simplified, you'll find robots are a candidate.
The main issues with robots in my experience is whether you can get the desired throughput while including planned and unplanned maintenance work, reconfigurations, etc. The upfront capital cost generally means you don't have the ability to have a drop-in replacement ready to go when a change is required. That results in downtime. Folk familiar with LEAN six sigma will know that hidden bottlenecks should be avoided or you build up large backlogs during downtime.
Good news for datacenter engineers is that fixing robots may become part of your remit in the future (interesting niche given the mix of software and mechanical). More interesting work will always exist!
- dv_dt 5y agoAre there any interesting mathematical or other tools that you recommend to evaluate hidden bottlenecks systematically? I wonder for example, about Toyota making a decision to add inventory buffer for chips vs other auto makers. Great decision in hindsight, but how did they evaluate that in context with other possible actions.
- pm90 5y agoThe only way to know for sure is by experiments/simulations. The heart of any competent operations team, whether its in computer systems or plain old logistics, is drills. You can't simulate every possible scenario, but you try to analyze and get an initial set, and the build that up as you run into actual production issues. What you want to avoid is running scripts for the first time in the middle of a disaster.
- wiml 5y agoFrom what I remember this (at least used to) fall under the heading "operations research", which spawned a lot of mathematical tools used elsewhere like queueing theory. Related terms include supply chain engineering, logistics, industrial engineering, and the general ideas of scientific management, Taylorism, etc.