How Real Time & Accurate calculation of OEE can increase your factory’s throughput by at least 20%

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Digital Business redefining scope of Manufacturing Operations: Overall Equipment Effectiveness (OEE), Cost and Capacity Utilization

HIGHLIGHTS:

  • Industrial Internet of Things emerged as the biggest enabler of Industry 4.0 initiatives
  • Smart Manufacturing: With focus on Capacity Utilization and Overall Equipment Effectiveness (OEE), increase your factory’s throughput by at least 20%
  • Invest in Industrial Internet of Things Platform : Progress to a Digital Business future through IT/OT Transformation
  • Get your machines, SCADA, DCS and Historians connected.

Learn how a large automotive component supplier drove up OEE and CU by 20% within days of going live on Datonis®

The Internet of Things or IoT is enabling all kinds of devices and machines around you to connect and exchange information with each other and with you. The Industrial Internet of Things or IIoT is the biggest enabler of Industry 4.0 initiatives in manufacturing facilities across the world.

So what is the biggest impact that IIoT can have on your manufacturing and what is the first problem that you should focus on in your Industry 4.0 initiatives?

The answer to both these questions is Capacity Utilization (CU) and Overall Equipment Effectiveness (OEE).

Capacity Utilization and Overall Equipment Effectiveness defined.

Capacity Utilization

Capacity utilization is a measure of the extent to which the plant is effectively loaded considering planned shutdown (maintenance, upgradations and other planned scenarios) and no demand kind of scenarios.
CU = (Effective Working Time – Planned Shut Down Time)/ Effective Working Time
As an example, let us assume a machine M1 is available for 8 hours in a shift. The machine was scheduled for planned maintenance of 30 minutes. In this case, Capacity Utilization is computed as CU = (480-30) / (480) = 93.75%

Overall Equipment Effectiveness

Overall Equipment Effectiveness is a Key Performance Indicator (KPI) that tells us how effectively a manufacturing operation is running. OEE is compiled from three data sources
Availability: A measure that tells us how much the machine was available and operational. As an example, let us assume the same machine M1 was available for a 8-hour shift. The machine was scheduled for planned maintenance of 30 minutes. It also suffered from an unplanned breakdown of 60 minutes. In this case, Availability is computed as

A = Operating Time/Scheduled Time = (480 – 30 – 60)/(480 – 30) = 390/450 = 86.6%

Performance /Productivity: This measures the process rate, i.e. the speed at which the machine produces. In the same example as above, let us assume that 350 parts are produced. And it ideally takes a 1 minute cycle time to produce a single part. The performance gets computed as

P = (No of parts * ideal cycle time )/Operating Time = (350*1)/390 = 89.7%

Quality: This measures the ratio of good parts as compared to the total parts produced. For instance, if 275 parts out of 350 are good parts, the quality will be

Q = 275/350 = 78.75%  and

OEE = Availability * Performance * Quality = 86.6% * 89.7% * 78.75% = 61%

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Calculating Overall Equipment Effectiveness (OEE ) using Availability, Performance, and Quality

Observations on OEE and CU.

It is evident that by first accurately measuring and then striving for better CU and OEE results in better production thus impacting both your bottom line and your top line. However, there are several challenges that manufacturing companies are facing.
• Plant managers rely on data that is reported by their production teams to arrive at CU and OEE. This process is tedious, time-consuming and error prone.
• In most cases, parameters like Availability cannot be correctly computed at all, unless collected from the machines directly.
• Manufacturing plants have a wide array of heterogeneous systems consisting of machines, SCADA, DCS and Historians making connectivity a huge challenge.
• Parameters like cycle times are often bloated. They are based on historical cycle times and may contain all kinds of allowances and buffers. Real cycle times can never be discovered without actually measuring and analyzing it automatically.
It is important to ensure that every machine is connected and A, P and Q are being measured. This is where the Industrial Internet of Things (IIoT) is of significant relevance.

Why the Industrial Internet of Things matters.

IIoT is a culmination of advances in sensors, machines, the rise of cloud computing and advances in big-data analytics. It has made connecting heterogeneous systems and machines simpler. It has made processing the ever increasing volume of data from machines possible. Investing in an IIoT platform is the first step towards effective OEE and CU.

You might have existing PLC, SCADA and DCS systems. These are complimentary systems to an IIoT platform (link to the article). If your machines are not connected to a PLC, SCADA or a DCS systems, you can still collect all the necessary information using an OPC server (link to the article here). The IIoT platform can act as the single repository for machine data generated across all your plants. This information can be analyzed to compute.
• Real A, P and Q.
• Identify real cycle times based on historical trends. Use that to correctly measure OEE and CU.
• Identify floating bottlenecks in your process.
• Perform loss time analysis, prioritize and fix them.
• Set the correct baseline for improvement initiatives.
• Track and sustain the improvement initiatives by working on reducing losses.
• Bring in sense of urgency on the shopfloor to respond to unplanned downtimes.

All improvement initiatives like Total Productive Maintenance (TPM), Lean 6 Sigma and others need a real baseline. Once the base line is established, it becomes easy to identify pockets of inactivity, nature of losses and improves availability and performance of machines. IIoT makes this possible. And provides this information in real-time therefore giving you the opportunity of immediately making an impact.

How can Altizon Help?

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Invest in Enterprise Manufacturing Intelligence (EMI) and leverage Datonis, Industrial Internet of Things (IIOT) platform for Digital Business initiatives – Remote Monitoring, Data Analytics, Downtime Alerts and Condition Based Asset Management

Altizon is an Industrial Internet of Things company focused on helping manufacturers drive value out of IoT. We offer the following solutions for CU and OEE.

• We provide a service that will help you get your machines, SCADA, DCS and Historians connected.
• We provide a highly scalable cloud based IIoT platform called Datonis®. Datonis® has been built from the ground-up with industrial connectivity in mind. Get your machines online in days.
• We provide ready applications to monitor your OEE and CU starting the day you get connected. Drive change immediately.

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