Sometimes things that look good “on paper” don’t end up working well in practice. For example a team can have better athletes in every position, a better coach, and a better record, but still lose to the underdogs. Everything from forms of government to business strategies to romantic relationships that seem fail-proof often fail. That’s because what’s “on paper” doesn’t always account for all of the variables that determine an outcome. Sometimes the best course of action isn’t the best decision on paper. Automated systems must learn to look past the facts that only tell part of the story.
Robots love rules
Robots are really good at operating within a defined set of rules; that’s what they do. This is what makes machines so great for factory work and tasks that require consistency and repetition. Simply set a robot to a chore and walk away.
But while machines excel at binary tasks like moving from point A to point B, they aren’t good at intuiting, recognizing subtleties and nuances, or piecing together bits of information. Robots and machines systems are limited by their programming. Even automated systems designed to make optimal real time decisions operate with only partial information.
The best option on paper isn’t always the best option
An article from IEEE Spectrum pointed out this flaw in navigation apps. These applications, such as Google Maps or Apple Maps, are designed to offer the best possible route for drivers. However, these apps can’t truly offer the best route because the best option on paper isn’t always the best option in practice. Ironically, navigation apps sometimes lead you astray.
There are 18-wheelers getting stuck on remote roads with hairpin turns. Travelers are rerouted to country roads avoided by locals because of ruts and steep grades. Multiple people using the same app to avoid traffic can create congestion and traffic jams. These applications factor in distance, speed limit, reported accidents, and classification of the street, but they don’t account for things like blind corners, events, hordes of children being released from school, popular cycling routes, and many of the other factors that affect travel time, safety, and your overall experience while driving.
It’s not just your map app
Navigation apps don’t really affect your factory. However, the flaw in these applications point out a shortcoming that applies to all machines — the decision making of an automated system can only be as good as the information contained within the system. The best option on paper doesn’t take influential variables into account.
People reporting things can improve the accuracy and effectiveness of navigation apps. Perhaps a similar human curation can help with automated systems in other spaces.
Your Indramat machinery doesn’t have to make decisions. It just has to carry out clearly defined tasks without variation. However, as manufacturing changes and factories get smarter, automated real-time decision making will influence more and more manufacturers.
Make sure that your machines are ready for whatever the future holds for manufacturing. Call 479-422-039o for Indramat maintenance, troubleshooting, and support.