Achieve Optimum Production Output through KPIs & Data Analytics

Leading and successful manufacturing companies manage their operations through the collection, reporting, and evaluation of critical business information usually referred to as Key Performance Indicators (KPI). Historically, this has been focused primarily on sales and financials. Additional KPIs often include total sales revenue, gross-margins, customer orders, order forecasts, raw material costs, sales by product or region, A/P, A/R, and industry specific metrics. Having fast and accurate access to this information allows managers to make key decisions about how to reduce Cost of Goods Sold (COGS ) and operating expense while improving top line sales.

There are a number of software tools available that allow businesses to collect, report, and manage this information; they range from simple spreadsheet programs to more complex ERP systems. However, the solutions available to collect, extract, analyze, and report business operating data are often plagued with issues. They can be complex, require excess time to collect and manage data, and can often have significant inaccuracies. These solutions are usually comprised of multiple, discordant devices and systems that do not talk to each other or have integrated analytical or reporting capabilities. The end result is that companies often begrudgingly choose to collect the minimal amount of data possible which leads them to operating in an unsure environment.

Manufacturing companies are hearing more about the Industrial Internet of Things (IIoT) and how they can acquire and analyze important data from their production systems, machines, and equipment in real time. Having access to this production data can be the source for getting a more detailed and accurate view of the operation. Just acquiring the IIoT data is not the solution to the problem however. The real challenge is knowing how to acquire the right data, analyze it in the context of the manufacturing process, and map information to the KPIs that indicate how the business is operating. The Prophecy IoT system provides the solution and expertise to achieve this higher level of “operational intelligence.”

Companies can take a look at how Prophecy IoT addresses the need to align machine and operating metrics with the resultant KPI desired. The first step is to know which KPIs are important and can give management clear and expedient information to make beneficial operational decisions. This can be a daunting task if companies have not practiced a KPI approach to helping manage production and operations.  With over 35 years of manufacturing experience and IIoT expertise, the Prophecy IoT team can help companies define meaningful KPIs.  Typical KPIs used for production often include:

  • Actual Finished Goods output v. planned
  • Actual Runtime v. machine downtime
  • Production Line Changeover time
  • Throughput (how much product is being produced on a machine, line, unit, or plant over a specified period of time)
  • Overall Equipment Effectiveness (OEE)
  • Capacity Utilization – Indicates how much of the total manufacturing output capacity is being utilized at a given point in time

 

Of course, there are many other production and machine KPIs that can be defined and measured. These are usually dependent on what the customers deem as important and actionable in order to make adjustments to improve the process.

Closely coupled to production activity is Quality Control (QC) and machine or equipment maintenance. Defining and measuring KPIs for these operational areas directly correlates to production procedure and process improvements. This can result in reduced machine downtime, less unplanned maintenance, less energy consumed, and improved product quality with less rework and scrap. The bottom line is a lower cost of production of goods to be sold.

After the KPIs are defined and data acquisition from machines, equipment and people, are determined, the next step is to define how the data is to be aggregated, reported and displayed. Effective KPI data reporting for the management team and displaying real-time manufacturing information to production and operator personnel is the final piece to overall production control and process improvement. Prophecy IoT has an integrated analytics engine with direct access to the acquired production and machine data. With no programming skills required, a customer of Prophecy IoT can create meaningful analytical charts, management dashboards, and Andon boards directly related to a company’s KPIs and reporting standards.

So, if the goal is to improve overall production output, uptime, and product quality, one can start by understanding the information that is necessary to collect in the form of KPIs and how best to analyze and report this data to take the action needed.  The Prophecy IoT team is ready to help.

Sample of Machine OEE Analytic Dashboard

 

Sample of Pie chart for Machine Yield %: