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Manufacturing Analytics Definition

Manufacturing analytics is a new class of software that brings predictive analytics, big data, industrial internet of things (IOI) and mobile first design to manufacturing companies.

What makes manufacturing analytics different is that it is purpose-built to handle the time series data manufacturing companies produce every day. Manufacturing analytics is focused on collecting and analyzing data rather than on process control. Data from an unlimited number of sources can be collected and correlated together to identify areas for improvement.

In the past, if you wanted to collect information from operators or machines on the shop floor, you would invest in HMIs (human machine interface), SCADA Systems, MES, Business intelligence, data historians, data logger tools etc. All of which are very complex, expensive to setup and maintain. But now with manufacturing analytics, you can buy a single software package to address your data collection and analysis needs.

Use of Manufacturing Analytics

There are a lot of things that you can do with Manufacturing Analytics. At its core, the tool is designed to provide performance and quality metrics. Below is a list of some of the most common scenarios manufacturing analytics supports.

  • Voice of the customer: Detect perceived quality and safety issues before they escalate.

  • Big data integration: Get a single, comprehensive view of all quality-related data.

  • The total cost of quality: It reduces scrap and reworks accordingly.

  • Predictive maintenance: It minimizes unplanned downtime.

  • Early issue warning: It quickly identifies design and production defects before they become widespread.

Manufacturing Analytics (MA) is software that brings big data, predictive analytics, Industrial Internet of Things (IIoT) and mobile-first designs to manufacturing companies. What sets MA apart, is that is purpose-built time series data that manufacturing companies produce on a daily basis. MA focuses on collecting and analyzing data instead of process control, and it is able to acquire data from unlimited sources which it can correlate to identify areas of improvement. Earlier, when one wanted to collect information from the manufacturing floor, it was a very complex and expensive process to set up and maintain. Today, however, MA is a single software package that addresses data collection and analysis.

MA enables massive amounts of data can be integrated and summarized into metrics that are simple to understand. These metrics are merged with dashboard components to provide access to data by role so that users can only see information that is relevant to them. When companies identify bottlenecks in their manufacturing process, they often turn to ERP systems; however, an ERP uses the best case scenario without any alternatives. An MA system learns from the data gathered and once it learns all the routing for particular parts and it identifies the bottlenecks, it will track, calculate average and, minimum and maximum cycle times, while also identifying any areas of improvement.

The tracking of the amount of scrap is important to any manufacturing company, using MA software; users can collect data directly from gauges and any other testing tools to automate the collection of scrap data. The specifications of the parts can be collected automatically from the gauges and get recorded as part of the production record, negating the need to input the values separately. The MA software uses formulated trends and algorithms in the application to identify specific parts that begin to deviate from the required specification and alerts the concerned teams.

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