Please take a look at this excellent video from Quality Digest called: “So God Made a Quality Manager”.
Recently we visited a company that had no automated system for collecting data, no system for SPC, and they were not monitoring process performance in their manufacturing plants (doing OEE). They do some quality checks once per day in the lab, and prepare a weekly report with some control charts, which they provide to their customers when they are asked.
They explained that they operate in a relatively unregulated industry, and the products that they make have been sold for decades to the same large companies, who once asked for quality data, but don’t often any more. They make a fairly unique non-consumer product that their customers need, and apparently buy primarily from them.
Sounds like a perfect scenario doesn’t it? A stable market, few competitors, and no need to improve or even really measure quality or manufacturing efficiency.
Life for some companies is indeed, good.
Consider this. The steel industry was once dominated by US companies. If you were the CEO of a US steel company fifty years ago, you had the largest car companies in the world (GM, Ford, Chrysler, and American Motors) as your customers, with relatively little off-shore competition. Your country was the fastest growing economy in the world, with an insatiable appetite for steel. You probably would have thought that there was no need to improve or even really measure quality or manufacturing efficiency. You sold all the steel you could make.
Today, there are 12 offshore steel companies before you get to the biggest North American steel company. 11 of the 12 are in Asia.
Somewhere along the line, the North American car companies came under attack from leaner, hungrier manufacturers that demanded high quality at great prices from their steel suppliers. Ignoring quality proved fatal for some of these North American auto organizations, and the America dominance of the automotive industry vanished, probably forever.
Massive consolidations in the steel industry followed, and all of a sudden, everyone was talking about Quality being Job-1.
Just because everything looks rosy today, that doesn’t mean that there isn’t a competitor eyeing your business and looking for weaknesses.
Don’t let quality be that weakness. Measure quality, analyse it, improve your processes, and measure again. And again. Never stop improving; it is the only way to survive.
Don’t be complacent about Quality.
The quick answer is probably. Like anything else, it depends on the current state at the company in question – but in 20 years, I have never seen a food processor that could not derive financial benefit from at-line data collection and statistical process control. There are many areas where just visibility to data can facilitate extreme cost reduction – some obvious, some not-so-obvious.
SPC simply recognizes that every process has built in variability. Monitoring variability and making information immediately available to the operator can reduce that variability. Reduction in variability (or to put it positively: consistent product) improves product quality. Improved product quality increases yield, and profitability.
In areas where variability from specification can cause failure in the final product, SPC has been embraced for decades – if the hole is too small for the bolt to fit through, the whole product fails. But in food, the ramifications of excessive process variability are not quite as obvious. In many ways, however, the financial ramifications can be far greater!
The following articulates some areas where our clients have observed significant savings; these may represent opportunities in your plant.
Net Contents Control is one of the most obvious opportunities, being both a “regulatory compliance” (cost avoidance) and “process improvement” (cost reduction) opportunity. Given that there is always variability in filling operations (despite claims we have heard of accuracy to .001 oz), there is an opportunity to have the occasional underweight get through or have a lot average lower than declaration – both of which are regulatory breaches. The standard procedure to fix this is to intentionally overfill; but this results in giveaway.
“So what if we overfill by a few grams?” you ask; “No biggy – pennies”. A couple of grams per package x packages per shift x number of lines x cost (or selling price) per gram can be an astronomical number – especially when extrapolated to the year. Tightening up the process by a single gram may pay for a complete plant system in a matter of weeks – with a coincidental increase in compliance! We have seen this time and again. And, although the studies were done over a couple of months with benchmarks from the first week, the most dramatic improvement is actually realized in the first few hours; derived from showing the operator her results – the rest is slow, methodical improvement.
Relying exclusively on in-line checkweighers to kick out underweights creates rework or feed – it reduces the symptoms, but doesn’t provide a long term or cost-effective remedy. And especially in an environment where the tare is highly variable, it is an inaccurate method.
Paper charts are tedious, and subject to human error. But most importantly, they do not represent useable data – they are simply filed away and never seen again at shift’s end.
Improved consistency ANYWHERE in the process can have a very significant effect on net contents. Too thin may give the consumer the impression that the package is underweight. In cereal, particle size is crucial – who wants a large amount of dust in the bottom of our cereal box – anything that can improve flake size, moisture, cook time can really affect fines. Certainly in cheese, moisture content can affect net weight… so much so that moisture is also regulated. The same is true, however, of any product that has moisture content. Water, being essentially free, is an excellent ingredient as long as it does not affect quality. What would be the financial impact of shipping 1% more H2O?
Temperature, for example, may be a HACCP/regulatory issue (as in internal temperature of meat), but too hot, or too cool, may also have significant ramifications to processing equipment farther down the line – everything is tuned to expect a certain temperature of product, and variation can literally gum up the works – causing scrap, slowdown, and downtime.
Understanding the impact of various process variables will result in process improvement which may range from shaving a few minutes off setup, to changing processes to increase throughput by simplification – all of which can keep your plant cost-competitive with other plants in the family, or competitors.
It is a truism that the more you know about your process, and the faster you know it, the faster you can adapt and avoid crisis. Typically process knowledge also reduces setup time – allowing more time for actual product processing. Often solutions are easy and inexpensive once you know what the critical process parameters are. Otherwise solutions are trial and error.
Food companies are beginning to embrace OEE as a key performance indicator, yet surprisingly most OEE systems available do not contain an integrated SPC system – that is like weighing yourself every day so you know how well the weight loss is going, but paying no attention to caloric intake or exercise. You may luck out, but if you understand the impact of 100 less calories or 20 minutes more running, your chances of reaching the goal are more likely.
Monitoring of cycle time can give visibility to improvement opportunity. Typically more consistent product can be processed faster, thereby improving yield. What is the value of increasing your filler speed by 10 packages/minute, or palletizing 5 minutes faster per hour?
Comparing results from multiple lines, whether process or packaging, will facilitate better scheduling decisions to match machine capability to product specification or demand. Even identical machines will have different variation characteristics which will make some products run better on specific machines or lines.
Alarming is also a significant savings opportunity. Often a specific measurement may be a leading indicator of problem potential further down the line. As an example, a 5 degree drop in temperature in mixing may cause problems in the later forming operations. Knowing that the temperature has been exceeded early will reduce the downtime or the waste at the forming operation.
And last, but not least, correlating process and quality data allows you to discover intra and inter process dependencies which enable effective planning and streamlining. You may find counter intuitive relationships: maybe an increased conveyor speed will actually improve product consistency by speeding cooling.
SPC – it’s not just for the automotive guys any-more.