Manufacturing analytics is a new class of software that brings predictive analytics, big data, industrial internet of things and mobile first design to manufacturing companies. As you read through this post you may think it is just another BI (business intelligence) tool, MES or SCADA system replacement. While there is some overlap between the products manufacturing analytics is in a class by itself.

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 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.

So what can you do with a Manufacturing Analytics?

Out of the box you can track OEE (Operational Equipment Effectiveness) for a machine, work cell, plant or the company as a whole. The system can collect data from operators or directly from the machines using sensors already built into the equipment. From this data you can measure different types of downtime, short stops, slowdowns etc. and produce trends. OEE, good parts, scrap and other metrics can be displayed on scoreboards over machines or work cells in the shop so operators and managers how they are performing.

Manufacturing analytics systems are smart they learn from the data they gather. For example, many companies want to identify bottlenecks in their manufacturing processes. There are a lot of ways to do this but most companies will turn to tradition ERP systems to find the bottleneck, this is problematic for a couple of reasons:

1. The ERP system usually represents the best case scenario and does not include all the alternates.

2. Many times the routing in the ERP is not what happens on the shop floor. Using a system like ODOO the system will learn all the routings for a part and identify the bottlenecks in each routing. It can track and calculate average, minimum and maximum cycle times for a part by machine, cell or the part itself helping you identify areas for improvement.

Tracking and reporting scrap is vitally important to all manufacturing companies. Using a Manufacturing Analytics package offers you a lot of flexibility and tools for reporting quality. Using the HMI (human machine interface) operators can record scrap reasons as they are discovered. PPTS also has the ability to collect data directly from gauges and other testing tools to automate collection of scrap data. Quality specifications can be collected automatically through gauges and recorded that as part of the production record. Using trends and algorithms in the application the system can identify when parts start to deviate from the specification and alert the operators or quality teams.

Collecting data is a wonderful thing but how do you use and make sense of it? This is where manufacturing analytics excels. Massive amounts of data can be consolidated and summarized into easy to understand metrics. The metrics are combined into standard dashboard components to help you understand what is happening in the shop. The dashboards provide access to data by role so users only see what is important to them and don’t get distracted by a lot of noise. As manufacturing analytics matures algorithms will be developed to automatically find anomalies and bring them to the attention of the correct people. Scoreboards can be displayed in the shop so everyone can see how a cell, machine or the entire plant is performing.

Small to mid-sized manufacturers are looking for data and the traditional tools don’t allow them to easily collect, analyze and display this information. Manufacturing analytics offers companies a way to affordably track and report the key metrics that will help increase the bottom line.

Manufacturing Analytics and Machine Analytics

With Advanced and Predictive Analytics we support a wide range of analytical questions. In most production and production processes, data can be collected and processed for the automatic generation of predictions. The following are some typical applications:

  • Prediction of failures or problems with machines and systems over a defined period of time
  • Minimize downtimes in production
  • Improvement of the repair rate at the first use of a technician
  • Identification of reasons for the failure of machines or systems
  • Prediction of production parts with errors (NOK / NIO parts)
  • Restriction of the reasons for the production committee

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