Machine monitoring software features Improve machine operator efficiency
In the manufacturing industry, the capabilities and expertise of an operator are being presented in terms of "Efficiency. An operator with higher efficiency generates more efficient products than an operator with lower efficiency in the same time frame.
Kharadi Pune, Maharashtra, October 11, 2021: In the manufacturing industry, the capabilities and expertise of an operator are being presented in terms of "Efficiency. An operator with higher efficiency generates more efficient products than an operator with lower efficiency in the same time frame. And when operators work with maximum efficiency, the manufacturing cost of the factory goes down.
Overall Labor Effectiveness, is a helpful manufacturing KPI for deciding the effectiveness of machine operators.
Estimating operator efficiency takes into consideration the time operators put in working, the number of parts they build and the quality of parts generated. It is similar to OEE but calculates the efficiency of the operator instead of the efficiency of the equipment.
For a more extensive productivity calculation, OEE should be utilized. OEE is best measured per machine rather than across the entire factory as it is then simpler to recognize where improvements require to be made to help increase productivity.
By having exact work standards, involving jobs, cycle times, manufacturers can have a better understanding of the predicted production performance they should hold operators responsible to.
Developing various programs depends on operator performance is a simple way to execute a friendly competitive system to motivate operators. In this way, all operators have an equal chance to "win" and as operators are performing above the standard, the industry is winning as a whole. Goal setting, as well as competition between workgroups or cells, can tremendously improve motivation and output.
With systems in place to interpret operator and equipment performance, managers will have a good understanding of where more opportunities exist. They can determine bottlenecks, areas of inefficiency & can recognize what shifts, jobs, machines and operators are high performing and which are not.
This data can be utilized to build stronger training material and utilize the successful aspects of the factory floor to assure that the less successful components have the tools required to drive productivity forwards.
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