Conservation of Energy

We will all be a lot better off in the industrial coatings world – longer performance, cleaner environment, healthier workers, and more profits/savings – when we truly embrace our work as a manufacturing process.  Cleaning (blasting) and painting is an energy intensive process. We overkill with air pressure and tons of abrasive (and paint over spray) in order to ensure we have to make as few passes as possible to meet the spec.  Air, paint, and grit are cheap compared to access and labor, so this approach is at least rational, if not efficient.

We’ve designed our equipment and our job logistics to accommodate this brute force approach, and most of the time, it gets the job done. But in the world in which I function (tech development and transfer), we are always looking to do things better, faster, safer, cheaper.  For the most part, we continue to hit the wall in the areas of coatings development, waiting for the next revolutionary materials breakthrough. Likewise, in access, containment and waste management, we have flattened out after the great advances driven by the lead paint efforts of the 90’s.  In surface prep, innovation has come in niches like UHP water, sponge, and water/grit combinations. All of these engineering accomplishments have moved the chains, but, honestly, have stalled out in the red zone.  Most of the time we are kicking field goals in our tech development efforts.

In order to improve our efficiency, we need to embrace process control. We need to KNOW what result we will get on the first pass of the nozzle or gun on the work piece AND know that that result is the same as the result on the last pass.  This must be accomplished through the development and use of DATA. The blaster has to know that with his particular gear, with the job-site setup, with the abrasive in the pot, on the type of steel, he/ she will meet the spec (or, more likely do far better than the spec requires). He/ she also has to know the relative effect of each of those major variables if they change. What variables can be compensated and keep the job moving? What changes mandate adjustment on the fly and which mandate a shutdown and reset? 

For the most part, only small bits of this type of data exist, but it is not beyond our collective capability to generate (or simply collect) it, synthesize it, and put it in a form where it can be used, built upon and improved over time. This is not QA data – which we spent A LOT of money collecting now – it is process control data. Data that is needed before the work is done so that the work doesn’t ever have to be redone.