Manufacturing Vocabulary (#2)
English 4 Engineers
Make to Assemble (MTA)
There are a couple of different types of manufacturing production processes. A make to assemble (MTA) strategy focuses on having readily made parts available but does not start making the finished product until an order has been placed. This allows for some customization, but not full customization like the make-to-order stategy.
Make to Order (MTO)
In manufacturing, this is a process where a product is only made after an order has been placed by a customer. Typically, these are highly customized and personalized products made to fit a customer’s specifications. Think about a custom piece of furniture or even a custom car – these are both examples of a made-to-order (MTO) product.
Make to Stock (MTS)
This is a traditional strategy followed by many manufacturers. Make to stock (MTS) creates inventory in anticipation of customer demand. This strategy does require an accurate forecast which is not always easy to do. If the forecast is wrong, manufacturers can be left with too much inventory or too little.
MTBF – Mean Time Between Failures
This is a traditional strategy followed by many manufacturers. Make to stock (MTS) creates inventory in anticipation of customer demand. This strategy does require an accurate forecast which is not always easy to do. If the forecast is wrong, manufacturers can be left with too much inventory or too little.
MTTR – Mean Time to Repair
MTTR and MTBF go hand-in-hand because while MTBF calculates the average time between failures, MTTR calculates the average time it takes to repair that failure. Again, this calculation varies from one company to the next.
OEE – Overall Equipment Effectiveness
A métrica mais conhecida na indústria de manufatura avalia disponibilidade, desempenho e qualidade para determinar a eficácia da máquina. Usando uma fórmula desenvolvida pela fabricante automotiva Toyota, o OEE é calculado multiplicando todos esses fatores para obter uma única métrica. Saiba mais sobre o OEE e o papel que ele desempenha para os fabricantes e a produção de bens.
OPC – Open Platform Communications
A series of standards that apply to industrial telecommunication, OPC specifies “communication of real-time plant data between control devices from different manufacturers”, according to Wikipedia.
OT – Operational Technology
Used by hands on the factory floor, OT is the software tasked with changing machine processes in a plant or factory. For example, the software can control the use of valves or pumps.
Pareto
Created by world-renowned Italian economist, Vilfredo Pareto, the Pareto principle states that 80% of consequences come from 20% of causes. In manufacturing, the principle can be applied to analyzing downtime. Generally speaking, 20% of causes affect 80% of downtime. Using data science, manufacturers can determine the top issues affecting performance. This data can be displayed in a Pareto Chart in real-time with Mingo.
Performance %
Often also referred to as throughput, performance measures the actual cycle time versus the ideal cycle time. Performance of a machine, cell, or line indicates the ability to meet the schedule or deliver to customers on time. Manufacturing analytics software can calculate performance by collecting part or product counts from the machines and compare them against the ideal cycle time in the system.
PLC – Programmable Logic Controller
Basically, this is a computer that has been modified or programmed, to be used for the manufacturing process. The controllers can specifically automate processes of production, machine function, or even an entire line.
Poka-Yoke
A Japanese term meaning “mistake-proofing”, Poka-Yoke pertains to any process in Lean manufacturing that helps avoid mistakes. Its sole purpose is to eliminate human error by correcting or preventing defects in products.
Quality %
This refers to the quality of the products currently being produced by a machine. Manufacturers rely on a set of metrics to determine the quality of a product. With manufacturing analytics, it’s possible to calculate the Quality of a part by collecting part count and reject reason codes then augment this information with input from human operators.
