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SOURCE: http://www.ge.com/digital/blog/12-manufacturing-tips-brilliant-2017-tip-1-manufacturing-physics
New year’s is always a good time to reflect and plan. So here’s the first in a series of manufacturing tips for having a brilliant 2017.
GE is executing its own strategy for developing brilliant factories that are digitally optimized to drive greater efficiency, productivity, and lower costs. In this brief series, I will share some stories of how analytics and data intelligence have been applied to discover inefficiencies or problems in manufacturing plants—unlocking new levels of performance and factory optimization.
Let’s start with manufacturing physics.
The psychology of the manufacturing organization can be predictable; employees tend to do whatever they are measured to do. Operators have production goals, and many times they are measured against each other. Results of these measurements of production throughput can have an inverse effect on plant maintenance.
In a heavy industry or complex discrete manufacturing plant, the culprits are sometimes the operators themselves. To their credit, they want to meet their production goal and exceed them. To do this, they will increase the feed rate of a machine they are working on. We know in physics that there is a relationship between velocity and force of impact. This takes the form of the equation K=1/2mv^2, where K is the kinetic energy imparted. m is mass, and v is velocity.
Therefore, the force of impact of an operating machine goes up by the square of its velocity or speed. The faster you go, the more your machine wears out and breaks. Experienced operators are better at increasing the feed rate; the problem is that less experienced operators try to replicate this activity, and that results in greater issues.
Operations shortcuts plague supervisors on production lines who need to watch and keep track of how their operators are performing and maximize the overall operation. That’s why it’s very important to have a tool that can calculate overall equipment effectiveness (OEE) in the context of production information and production rate.
By analyzing this data and looking at it over time, supervisors can come up with the optimal rates versus maintenance schedules for their machines and their portion of the plant. They can also keep tabs on worker productivity versus maintenance costs. This also allows the operation to make better, smarter goals for workers to balance all the needs of the plant.
Better living through data analysis and analytics is the mantra of a Brilliant Factory.
