Using OEE and IIoT to Eliminate Manufacturing Waste

3 minutes to read

Vecna Robotics’ AI and IIoT Delivers Immediate Corrective Action

Overall Equipment Effectiveness (OEE) is a quality systems management tool that enables a manufacturer to assess the effectiveness of its equipment based on the combined acquisition and assessment of three metrics: availability, performance, and quality. Using OEE as a tool, manufacturers can identify major losses.

Until the recent convergence of Artificial Intelligence (AI) and data analytics tools, OEE measurements and the Industrial Internet of Things (IIoT), no plant manager could create a roadmap to enhance productivity and throughput. Solutions today, however, must provide quantifiable evidence that manufacturing equipment is operating at maximum effectiveness. Plant managers need actionable insight into equipment availability, performance, and quality output.

Basically, you can’t fix it if you don’t know it’s broken. Manufacturers have to know where problems are located. Data collected from IIoT installations allows Vecna Robotics customers to identify issues and gaps in efficiency and pinpoint exactly where those issues lie: with equipment, with employees, or a combination of the two. AI and advanced analytics help to speed the data collection and evaluation process, eliminate human error, and put continuous improvement processes in place.

Through equipment inefficiencies, plants can incur billions of dollars in waste including costs of increased labor, overtime charges, penalties for late product, lost sales, lost customers, cost of quality and scrap, and extra production to compensate for equipment failure. Vecna Robotics incorporates OEE to reduce or eliminate such costs by identifying causes so that corrective action can be implemented.

OEE addresses six root causes of loss: breakdowns; setup and adjustments; idling and minor stops; reduced speed; startup rejects; and quality defects and rework.

In a typical manufacturing environment:

  • Breakdowns occur regularly
  • Temporary repairs are the norm
  • A run-to-failure mentality is predominant
  • Constant adjustments interrupt production
  • Minor stoppages occur frequently
  • Processing speeds decrease
  • Operator training often is inadequate

And, because no one is charged with tracking these losses, no one is held accountable

Saving just 20 minutes a day in staff changeovers could pay the salary for a plant manager.

OEE looks at availability, performance, and quality of each individual machine, which is automatically assessed against the whole in complex production equipment. Availability equals operating time/planned production time; performance equals total pieces/operating time/ideal run rate; and quality equals good pieces/total pieces.

Translated into numbers, a very good OEE is considered to be 85 percent, with specific metrics achieving rates of:

  • Availability — 90%
  • Performance — 95%
  • Quality — 99.9%

Because each metric has an impact on the others, the total is less than each of the parts.

Implementing the full scope of OEE requires intelligent use of those metrics. Organizations must assess the collected data, determine the cause of equipment inefficiencies, and implement corrective action. Collecting and using this data used to be difficult and time-consuming – but times have changed.

The combination of AI and IIoT is giving leading-edge companies a distinct competitive advantage. The old school automated guided vehicle (AGV) is no longer good enough; A holistic workflow focus including advanced data-driven continuous improvement must be adapted and transformed to keep up with modern manufacturing practices. Vecna Robotics is the first robotics manufacturer to offer embedded 24/7 IIoT monitoring, driving operational efficiency and improving OEE.

Read more about Vecna Robotics’ cutting edge technological innovations here.