Within the last year, I’ll bet you’ve heard at least one ‘new’ wonder-product being touted as Smart. And then said to yourself—is this one any different than the other developments of the past 20 years (MES, MOM, PIMS, CIM, ISA-95, etc.)?
Will it actually make a difference to my people, on our lines? In particular to the decisions we make and the results we earn? Is it really Smart/Industry 4.0?
I’ve been pondering the "What actually defines Smart?" question a long time. Today I’m going to share with you what I’ve come up with, plus three real-world examples. Here we go …
What is Smart, Really?
Smart manufacturing is actionable information and insight brought to the right person at the right time to improve what they are doing (not just in process control) through a feedback loop.
Areas of improvement include efficiency, production, quality, energy, raw material consumption, inventory and, out of the plant, the supply chain. Again, we are talking about much more than process control.
Smart takes feedback to a whole new level. With more sensors, on more things (more cheaply and easily), you can interconnect the information and get insights with analytics—figuring out interconnections that were impossible before—so as to provide far more deep, sophisticated feedback.
This sophisticated feedback is the essence of Smart Manufacturing / Industry 4.0. Anything else is just hype and supplier rebranding.
What I call Dumb 4.0 is defined by absence of insight—after-the-fact, non-actionable information, lacking an actionable feedback loop to the right person.
Now, as promised, three examples of Smart/Industry 4.0 versus Dumb 4.0 (or its twin, Hype 4.0).
Example 1: OEE (Overall Equipment Effectiveness)
Dumb 4.0 OEE solution
Many suppliers (and almost all multi-million ERP suppliers) give you an OEE report at the end of the month. It’s a measure of the efficiency of your assets. But it’s a dumb report, a rear-view of what is long-gone and over. You have no chance to change or influence these results. And there’s no insight. A feedback loop at the end of the month is continuous frustration, not continuous improvement.
It reminds me of an MBA that I fired many years ago. He claimed he could always predict any financial failure, but never contributed to improving the company financially. One more Dumb OEE app is an MES (Manufacturing Excel Spreadsheet). If you’re working from one, start figuring out how to abandon it, ASAP. It’s holding you back.
Smart OEE solution
A smart OEE software application is event-driven and provides real or quasi real-time information during the shift to the operators, supervisors and maintenance people. This drives improvements in quasi real-time as well as enabling offline root cause analysis for continuous improvements. For instance, if the machine speed is not set up according to set-up parameters, this will be flagged to insure optimal OEE during the shift, not at the end of the month.
OEE story: One OEE case I worked on involved a paper machine. The data showed that if you increased planned maintenance (reducing available production time), quality improved, thereby reducing waste. In other words, the machine’s overall OEE was better with less available time running. This could not have been discovered without analytics.
Example 2: Giveaway
Dumb 4.0 giveaway solution
In the food industry and consumer packaged goods, regulators impose heavy fines on any manufacturer putting less in a bottle or a box than the quantity shown on the label. If the box says 1/2pound or 500gr, then that amount, at the least, has to be there.
Giveaway is Inevitable. Production lines always put in extra – the minimum amount over that is consistently achievable by their process. Lots of giveaway, every shift.
I have seen end-of-month reports that inform management of the spectacular amount they give to customers for free – without any insight on how to run the process more tightly and reduce giveaway. That’s continuous frustration, not continuous improvement.
Smart / 4.0 giveaway solution
We helped a producer of snack foods set up real-time dashboards for operators that displayed the 20% of parameters that had an 80% impact on giveaway. Any time a parameter was not within specs, it was highlighted in yellow or red. Again, that process intelligence was a result of analytics from shop floor information and historical data. The improvement was almost instant, as the operators knew, all day long, which lever to push to stay within range on these critical parameters.
Bonus: The dumb giveaway report that had cost them a fortune confirmed that the Smart stuff was doing its job very well!
Example 3: Quality System
Dumb 4.0 quality system
Have you ever received quality results once the product has already shipped to the customer? And were the results put into production context (by shift, machine, product, recipe)?
If not? Your quality feedback loop is the complaint department, as well as products shipped back to the plant. Your customer is the route you have chosen to detect poor quality—never a good plan—and the data you get is out of context, out of phase with production, and unlikely to spur improvements. Quality management in Dumb 4.0 is akin to firefighting: lively and crisis-driven, but wasteful.
Smart quality system
How fast can you close the quality feedback loop to the shop floor? Can the operator act with this data? In the longer term, can you do root cause analysis to improve? If yes, you have a Smart quality system. If not, file it under Dumb 4.0.
Bonus: Anything that is truly Smart, or Industry 4.0, enables continuous improvement. Not just something new today, but the opportunity to make ongoing improvements to productivity. If the product or service you’re looking can do that for you, it’s likely Smart. If not? Dumb dumb dumb!
Charles A. Horth is the chief executive officer of Factora, a Manufacturing Execution System (MES) consulting firm that uses software to solve factory problems.
