Smart Manufacturing more than Smart Metrics

The manufacturing industry has been hearing a lot about the Internet of Things (IoT) and Industry 4.0 in recent years. Principally, IoT should enable manufacturers to make things better, faster, quicker and more sustainably. However, David O’Keeffe, Operations Manager at contract electronics manufacturer (CEM), Trojan Electronics, believes connectivity should not be prioritised ahead of customer value.

He explains: “It’s clear that as manufacturers we are driven to make things that perform better, quicker or more sustainably. However, as manufacturers, we rely not only on the use of expensive capital equipment (Capex), but an often diverse and / or complex supply chain and the ability to obtain maximum efficiency from both our operational and production teams.

“Proponents of IoT and ‘better connectivity resulting in better data utilisation’ suggest that connectivity harnesses that all important data enabling manufacturers to achieve better asset utilisation. The reality is somewhat different and dependent on several additional factors including the type of production and location of your business.

“For example, retrofitting every piece of kit with smart sensors in a typical CEM would require significant investment. That is before there is even any mention of the cloud-based architecture the wealth of data captured will rely on or the upskilling of your production and operational team.

“Whilst I agree that full asset utilisation is important, we need to think instead about (1) what we are trying to measure and why and (2) how this enables us to deliver maximum value for our customers.”

Key metrics in manufacturing include overall equipment effectiveness (OEE) – the percentage of manufacturing time that is truly productive, and downtime analysis (DAD) – accurately analysing downtime and downtime loss.

Consequently, this assumes that by capturing the right data, manufacturers should be able to drill down to individual lines or equipment as required to provide a root cause analysis for any issues whilst providing key financial data which would inform future planning. Fair enough.

If your manufacturing business relies of both hand placement (manual assembly) and machine fitting components (automation) or even refitting components, the data that matters needs to include several other variables, including:

  • <span “>utilisation of uptime
  • <span “>pick and place
  • <span “>quality statistics for hand placement components per minute/ hour.
  • <span “>Reliability e.g. right first time
  • <span “>Amount of time spent reworking components, etc.

 

As such, it is just not as simple as “sweating the assets to save time and money” as some cloud-based web service providers are suggesting according to O’Keeffe.

From the above, it also makes it far more important to maximise reliability and quality rather than measuring throughput or output he says.

“Any investment of this nature would unlikely bring an immediate return on investment, contrary to what these web service providers are suggesting.”

Projects of this nature are further unlikely to be “discrete” and easy to achieve added O’Keeffe.

“Although the ability to predict failure patterns before they happen sounds good, good operational management already include predictive maintenance and optimised servicing schedules.

“Thus, rather adding more sensors to get more data from machinery, manufacturers should consider instead of what their customers value.

“For example, recycling component parts to make certain boards more economical, setting up an integrated and robust supply chain and flexing to provide more than one solution for a product assembly all matter more to customers than how many parts are produced in a day/ week or month.

“Rather than ‘Smart’ asset management, this is smart manufacturing focussed around building value and trust in a very uncertain world. Longer term, this is what effects the real bottom line rather than fixating on the uptime of operations.”

 

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