When I first got hired, we had a lot of messy desks with a lot of material. Their self-made excuse was they could find everything they needed and only went to the stock room very rarely. This way they saved time. Then I parked myself in the middle of the lab with a stop watch. It turned out that we spent less time going to the stock room then looking for anything in a messy desk. 3 weeks later and 5 boxes (5'x5'x5' boxes) of trash we actually have desk space to work on. Now we only order what we need. No searching as everything is ordered in Microsoft access. And you don't lose your current project to a trash avalanche.... Now I was lucky some one senior to me listened and agreed with throwing everything out. Later he forced everyone else to participate. To this day people still complain how they could find things in an instant before the cleanup. Junk that you will not use the next 6 months, 1 year, 2 years should not be saved but rather recycled. It should all be proportional to its value, size, and frequency of use.
I recently won a "clean desk award" at work, which was a source of amusement to my co-workers, since, as a failure analyst, my desk is covered with broken parts. (Although it is nothing like the desks in this slideshow!)
On the other hand, there were no confidential documents on my desk, which is what the clean desk police were looking for. Other co-workers, who have otherwise immaculate desks, were denied the prize because they had a phone list next to their phone -- apparently, our phone list is confidential.
The prize was a free lunch in the company cafeteria -- who says there's no such thing?
My take is this: there is a messy desk, and then there is a messy desk. One messy desk is piled with data from past projects, white papers, spec sheets, etc., basically a free air open-looped file cabinet. That is geniune messy. In another blog post I stated messy desk vs clean desk are two different information management strategies. In the end the benchmark is how much time it takes to find whatever is being looked for. THEN there is a messy desk. That just needs to be cleaned up. I'm sorry, I see that coke cans and serpentine tangled phone cords are not included in the true spirit of the open-looped free air information management style of our revered engineering forefathers.
Voigt's "workspace" is unbelievable. I guess it could be worse--there are actual aisles between the piles--but doesn't it take at least as much time to find stuff as it does to work? Aside from that lost bill, I eventually became a neatnik in my office, workshop, and kitchen because I hated having an inspiration and then not being able to do it for want of finding the tools. By the time I found the tools/backup info/whatever the inspiration might have disappeared and I was an unhappy, frustrated non-creator.
I used to have a filing system: "Newest on the top; oldest on the bottom." Then our company adopted a clean desk policy -- for security of intellectual property. I got organized and cleaned up my act and found that I liked it. I adopted a new policy of tearing up failed experiments. If I wanted to keep an article I tore it out and filed it where I would use it instead of keeping the whole magazine.
Engineers are lucky not to have to abide by HIPAA confidentiality law that must be observed by clinics and hospitals. If they work with such clients they must understand their role in keeping confidential info locked up.
Are they robots or androids? We're not exactly sure. Each talking, gesturing Geminoid looks exactly like a real individual, starting with their creator, professor Hiroshi Ishiguro of Osaka University in Japan.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.