Manufacturing processes can, on the surface, appear to be an amorphous web of convoluted conveyors and machinating machinery. But taking a closer look through the eyes of a quality engineer reveals that the process that leads to reliable products is, in fact, itself a series of decisions, each compounding and building on every preceding action.
Breaking down the interrelated processes within a production system is crucial to isolating issues, getting to the root cause and efficiently implementing solutions.
Our manufacturing processes are getting smarter. To keep up, manufacturers need to gird their production lines with intelligent sensors and monitoring equipment that will allow them to make each of those interdependent decisions based on critical data. Informed decisions enable engineers to coordinate a process that ultimately has zero defects and outputs products that have no risk of recall or warranty claims.
In order to actualize an Industry 4.0 dream level of efficiency and productivity, manufacturers need to assess their current processes. They need to recognize their production gaps and the places they don’t have visibility, and then install quantitative measures to generate actionable data.
Read on to learn more about where those gaps can easily exist in manufacturing processes in any industry and the good news for manufacturers who intend to do something about it.
Here are some collected statements from BTG Labs customers during Adhesion Processes Surveys we’ve conducted:
Implicit in each of these remarks is a process gap that exists because of a lack of visibility at a particular (and vital) aspect of manufacturing that can make or break each of the described processes.
The vital and overlooked process element is the quality of the bond surface. If the manufacturers had looked to the material surface itself to solve their surface adhesion problems, tens of thousands of dollars and hundreds of production hours could have been saved.
To learn how to conduct your own root cause analysis using contact angle measurements, download our free eBook: Checklist: Adhesion Failure Root-Cause Analysis for Manufacturers
All of these manufacturer’s were experiencing adhesion problems in their process. Whether printing, painting, coating, cleaning, sealing or bonding, they all had instituted some kind of surface preparation, cleaning or treatment process and conducted these procedures as instructed by the equipment or adhesive vendors. This fact begs the question, why was that not sufficient?
If we add a measurement of surface quality to the equation, we can predict a different outcome in each of the four examples:
Manufacturer’s who paint, print, bond, coat, or seal have been left in the dark when searching for answers to solving their adhesion problems.
But there's a light at the end of the tunnel.
To illustrate the dilemma manufacturers routinely face, let’s examine one manufacturer’s struggle to solve peeling paint in their operation. The main objective was to solve a common manufacturing problem, with a not-so-common solution.
Process Objective: Eliminate peeling paint that’s resulting in considerable rework and lost production time.
What approaches were taken by the manufacturer to solve the problem?
All of these responses to adhesion failure seem reasonable on their face as they are the customary solutions to these sorts of problems. But, there’s a distinct error hiding behind these solutions.
Nothing empirical can be decided until the material surface being treated is itself fully understood.
Making changes to the process itself, without using quantitative, real-time data that elucidates how your processes are actually affecting the material surface, means you will have no way to predict the outcomes of your process. Manufacturers making adjustments to surface critical processes without measuring the impact won’t know if their changes were meaningful until they do performance testing way downstream. By that point, it will be incredibly difficult to conduct useful root cause analysis to pinpoint the upstream step that wasn’t meeting the requirements.
Measuring surface quality at every Critical Control Point, or any place in the manufacturing process where the surface has an opportunity to change in any way whatsoever, is the only way to collect data for precise root cause analysis.
Predictive analytics that indicate with certainty that a cleaning, treatment or preparation process is creating bondable surfaces within the tolerances of the performance standards, is the only way to guarantee reliability.
The search for a reliable, repeatable, objective method for measuring surface readiness for adhesion and cleaning processes has been a source of immense consternation for manufacturers. The methods most commonly used leave much to be desired as they do not provide ample information about the effectiveness of surface preparation, cleaning and treatment processes.
As was outlined above, the difference between a process that consistently produces average products as opposed to completely reliable, industry-leading products is a process that has an appropriate, optimized and monitored surface preparation process.
The only way to truly know if a given adhesion process is on one side of that spectrum or the other is whether or not it considers the impact its procedures have on the top 3 molecular layers of the material surface being worked on.
So, since achieving predictable adhesion is dependent on such a thin and delicate layer of the material surface, it follows that the need for a highly sensitive, accurate, objective, and Materials Science-based measuring system is the order of the day.
Let’s take a look at the most commonly employed methods of surface evaluation to see if they measure up.
Method: Commonly the standard in the aerospace & automotive industry, this method involves spraying a surface with water and observing the behavior of the water as it runs off the material.
Drawbacks: Subjective, qualitative evaluation of water. Essentially a “quick and very-dirty” method of evaluating cleanliness. Offers no quantitative value and no information concerning how close the part is to failure. This method is possible to do in-line but is most often done in a secluded area since it’s rather messy.
Method: Commonly the standard in the film & flexible packaging industry, this method involves placing a stripe of hazardous, colored ink onto the surface to visually observe how the ink wets out or beads up on the surface.
Drawbacks: Subjective evaluation of a destructive ink. Often gives false positives since the ink includes a solvent that can cut through contamination on the surface and will react as though the contamination is not there. Dyne ink behavior is difficult to consistently assess and often the interpretation of how it reacts to the surface can change depending on who is implementing the test.
Method: Commonly used in labs for obtaining water contact angle measurements. This method measures two points of contact of a water drop resting on a surface by taking a side-long look at how much the drop wets out or beads up on the surface.
Drawbacks: Not as accurate or reliable as a top-down measurement that can take 64 simultaneous measurements of a deposited drop. Traditional goniometers can potentially offer misleading data due to undefined edge lines at low contact angles. Moreover, these instruments are not viable for mobile or real-time production testing.
Method: Through no fault of their own, some manufacturers still have not been able to find and/or implement a reliable, repeatable, practical and objective way to measure surface quality and therefore have little more than a visual “does it appear clean?” test before sending parts downstream where hopefully strength and performance tests will catch any problems.
Drawbacks: Manufacturing processes are inherently “out of control” due to a lack of monitoring processes that accurately keep an eye on variables that impact surface quality and adhesion success. Final product quality is completely left up to chance with no way to measurably reduce scrap, predict performance or build new processes that are at low risk of failure.
There is a method of surface quality measurement that actually provides a numerical evaluation of exactly what matters to the success of adhesion problems. Moreover, it can be implemented directly on the production line, near the action, to serve up data derived from looking at real parts in real time.
A simple contact angle measurement deployed through an automated or handheld surface energy measurement system is the most accurate and rapid way to mine your process for predictive analytics to put your products on the right course.
These measurements are conducted by depositing a tiny drop of liquid on a surface and measuring the angle the drop makes with the surface. If the angle is high (i.e. >~70 degrees depending on the material and application) this indicates that the surface is not very reactive as the liquid is repelled by it as opposed to being attracted to it. If the liquid wets out and creates a low angle (i.e. <~50 degrees depending on the material and application) then this indicates a reactive surface that is ready for adhesion.
When contact angle measurements are taken with devices that are built for the factory floor so that series of inspections can happen in mere seconds and results can easily be tracked to show quality trends, then manufacturers have a whole new level of visibility into their process.
Smart sensors that prove the effectiveness of cleaning and treatment steps while also providing crucial information about the base-line quality of surfaces as they enter a facility or a process puts manufacturers at an unprecedented advantage. Cleaning equipment and treatment systems can be optimized to precisely clean surfaces and make sure they are, without a doubt, ready for adhesion.
Accomplishing these is a reality because, through contact angle measurements, accurate surface energy data can finally be attained while parts are actually going through the production process. Surface energy is a chemical characteristic that refers to how reactive a surface is and therefore how strongly it will bond with another substance (e.g. paint, epoxies, UV curing adhesives, inks, a molten metal in the case of brazing or soldering, etc.).
All of the traditional methods are attempting to evaluate surface energy as it is the most precise predictor of adhesion success or failure. All of them fall short, however, due to limitations in giving useful data (if any at all) that accurately correlates to surface energy and the inability to be implemented where it’s most necessary, on the factory floor.
Let’s illustrate the way that accurate surface quality measurements can subvert expectations by revealing insufficiencies in cleaning and treatment that less sensitive methods habitually miss:
The link between these examples is that the quantitative surface quality inspections exposed unforeseen inadequacies with common preparation and treatment methods. If additional inspections are conducted throughout the manufacturing process of the material surfaces discussed above, then finding the root cause of the anomalous number changes is possible. It all comes down to measuring surface quality at every point in the process that could potentially alter the quality.
To learn how to conduct your own root cause analysis using contact angle measurements, download our free guide on how you can get started today. In our eBook “Checklist: Adhesion Failure Root-Cause Analysis for Manufacturers” you’ll receive step-by-step guidance on how to take a closer look at your process and ensure it is free from the most common quality gaps.