NOTE: This document is provided for historical purposes only.
Presentation by Bill Marras, Ohio State University
DR. PEACOCK: Bill Marras, many of you know. He is the NCR Professor of Ergonomics in the Department of Industrial Welding and Systems Engineering at the Ohio State University where he is the Director of the Biodynamics Lab. He also holds joint appointments in the Departments of Physical Medicine and Biomedical Engineering. He received his Ph.D. in Bioengineering and Ergonomics from Wayne State University in Detroit. His research centers around industrial biomechanics. He had published 80 reference journal articles and 12 book chapters and holds two patents, one of which is his lumbar motion monitor, and many of you are familiar with the LLM.
His work has attracted national as well as international recognition and recently won the prestigious Swedish Volvo Award for low back pain research as well as Austria's Vienna Award for physical medicine.
DR. MARRAS: Thank you, Brian, good afternoon to all of you. Today, I'm going to talk about some of the tools that are used to help quantify product design. What I found in my experience in product design is it's more than simply common sense. People are saying things like, ergonomics is all common sense, anybody could do it. Well, I would challenge that assertion. What I found is often by quantifying design, product design, you find that you get some really unexpected results. My contention is that you could not really come up with an optimal design until you do quantitative analysis.
What I'm going to talk about in particular here today is the design of something that's very common in industry which is case design. In particular, I'm going to talk about some issues in food distribution warehouses which are very common around the country. If you look at the injury rates, they're phenomenal. Warehouses are very dangerous places for the back, and at least most of them, you see typically over 30 percent of the injuries related to the back. It is common to see in the neighborhood of 60 to 65 percent of injuries related to the back.
Now, in order to control these costs in the food distribution area, the Food Marketing Institute out of Washington, D.C. came to us a couple of years back and asked us to do some quantitative analyses of some suggestions that they were ready to make to the industry. They wanted to limit the size and the weights of the cases that came into the food distribution warehouse and in turn are shipped out to individual stores.
As you can imagine, this is a very expensive proposition. They would require that, cases for example, be no larger than a given amount of weight and limited size. They also had some ideas about handles. All that could cost the manufacturers millions of dollars, they realized that was an expensive proposition. If they were going to make these types of recommendations and set standards, they'd better be right. These situations lend high cost to the decisions where you want to do quantitative analyses.
They contracted our laboratory to do this type of research, and I'd simply like to share some of our experiences with you. Our objective was to provide a quantitative assessment for the Food Marketing Institute and to look specifically at the risk of low back disorders. When they originally came to us, they said, "Well, we're considering a little drop in the case weight and we want to know whether 40 pounds is the correct weight or whether it should be 50, or 60, or whatever. We want to see the difference. We want to see a bang for our buck, because this is a very expensive decision".
They said, "We're also thinking about limiting the size", and they were pretty much basing these ideas just on what they'd read in the literature, what other companies were doing. They really weren't doing any quantitative analyses. When they approached us, we said, "Well, this is all well and good. We could do that, but have you ever considered looking at some other issues? For example, do you want to put handles in there?" The NOSH Lifting Guide, the 1991 revised equation has an effect for handles in there. So we suggested they might want to look at that.
We also realized that it's not just the way you lift the boxes, but it depends where you're lifting that box coming from and going to. So we were able to talk them into looking at that also.
Here are the cases we looked at. We wanted to be able to change the weight, and only the weight; and then change the handle conditions, only the handles. What we found was about the ninety-fifth percentile box in a warehouse and about the twenty-fifth percentile box in a warehouse. This happened to be a box of water containers in a box of salt. The nice thing about these is you could take some of the water out, take some of the salt out, maintain everything else the same and just alter the weight. Then we had a set of boxes that had handles and ones that did not have handles, and you can see we sealed them up pretty good so they wouldn't leak all over the place.
Where do you lift from the pallet? As you probably realize in most distribution centers and warehouses, basically, the task is to take boxes out of a slot and dump them onto a pallet jack. Essentially, you walk around with the shopping list and pick five boxes of this, 12 boxes of those and go back to the pallet jack and load them up. And so, when you do this you're constantly breaking down the pallet. You might start up here in the top regions and end up down there. We wanted to look at the risk as a function of that.
Our subjects were experienced warehouse workers, and I'd encourage people considering this type of work to use experienced people. There's a world of difference between a university student and somebody who is actually out there doing this all day long. You could see our experience averaged five years, and it went up to 23 years for at least one of our subjects.
The experimental task was simply to do what these people did every day. They simply came to our laboratory. We had set this up like a warehouse. We went to a warehouse, measured everything, measured the distances between the pallets, measured the heights of these. We also put slots in there that looked exactly like the slots in a warehouse, and we paced the person. We found out that in this particular warehouse we were emulating, they lifted 125 boxes a minute. So we'd have the person walk up here, stand on a tape mark, walk over to the slot, pick up a box, twist, turn, move it over to where the pallet jack would be, and that's where we ended the analysis.
While they were doing that, we were monitoring lots of things about the person. I'll show a little bit about this in a moment. Basically, we were considering everything on-line on the computer as well as videotaping everything the person was doing. This allowed us to really break the exertion apart.
As Brian was also saying in his introductory remarks, ergonomics is more than just worrying about biomechanics. You've really got to look at the total package, and that's one of the things we've recognized for a while. And so, this is the way I view the world of back pain. Biomechanics will get you so far, you could talk about the loading of the spine, things like that. But we also know there's some type of a social interaction involved here. Why do some people report higher rates and other people do not report high rates. We think there's some interaction between the biomechanics and that.
In order to explore that area, we've developed some technology based on historical trends. What do people like in the warehouse or in industry in general? What do they not like? When do people tend to report injuries versus not report injuries? And so, this is based on purely six years of observation of injury rates in industry, and we used our lumbar motion monitor technology with which some of you may be familiar. I'll talk more about that in a minute.
On the other side, we did have to pay attention to the biomechanics of the situation. We had to look at the loading of the body and the personal tolerances. In order to do that, we wanted to look at some bio-mechanical models that we had developed. I'll also talk about that in a minute.
First, in terms of the risk model, the historical perspective, that's basically what this is about. Our tool is based on historical observation in high and low risk jobs in industry for low back disorder. We looked at over 400 jobs in industry, divided them up into high risk jobs of injury over 12 instances per 100 workers doing the job per year, and then those jobs where there was a lot of material handling but didn't have any injuries. Given these parameters we collected in the workplace, we developed a model that helped us discriminate between the high risk jobs and the low risk jobs.
Here's the LLM. It's an exo skeleton of the spine, it straps onto the person. As they move around, it simply sends signals to the computer which tells us what the motion patterns are like.
This is the model. Basically, we found that five factors you get from the workplace such as lift rates and moments as well as some things you get from the LLM such as twisting velocity, lateral velocity, and sagital angle --- will determine what the odds ratios of what your risk or the probability of being in that high risk group is. The idea of this is when you're designing the jobs, get this vertical red arrow as far to the left as possible. If you're up here, you're almost guaranteed to have a back injury with that design of the job. If you're here, you're almost guaranteed not to have a back injury from the work.
Our other measure was a bio-mechanical model that we've developed over the last dozen years, and bio-mechanical models basically estimate the amount of load that occurs in the spine. Here's a vertebral body. There's a vertebral body. Here's a disc. What we're really measuring is a crush strength where the crush force is acting on the spine. It's the same way a lot of people do it, but ours is really a dynamic model.
Here's a representation of the model. We assume that there's a plate in the thorax, a plate in the pelvis, spine in between. If we know what's happening with all these muscles or vectors that are holding these two plates together, we could work backwards and compute the load on the spine, basically that's what we did. How do you measure the muscle activities? You do it with the electromyography, some of the slides that Rob had shown a little while ago.
Let me show what this model actually looks like and show you some examples. Here's the exertion we're interest in. We're interested in this fellah just lifting and lowering as you see right here. First, I'm just going to show you the basic model, and then I'll show you some specific examples of the things we're interested in. Just to show you how we could pick this model apart, we have hundreds of analyses at our disposal with something like this.
The first thing we may be interested in is how is the person moving it? We just pick up a couple variables. We'll look at angle and velocity, and there it was, the blue line. Up here is the velocity. The black line is the angle, you see there. As we move through time, the red line corresponds exactly where the video is. So we could see exactly how he's moving at any point in time. By the way, this the bio-mechanical model I'm talking about right now.
We could also look at the future such as how hard are all the muscles working? He's the EMG of the 10 trunk muscles we're monitoring, so we can have an idea of how those vary as a function of the work the person's doing. We could also look at how those co-activate. And what we mean by that is let's try and get an appreciation for how these all turn on at the same time. By looking at a cross-section of the trunk, here's the spine, here are the various muscles. We get a time history of how active those muscles are, so we could appreciate whether they're working at the same time or whether they're not and the different colors correspond to how intense the muscle's working at different points in time.
We could also get an appreciation for what this means in terms of the loads on the spine. As you probably realize, the distance from each one of these muscle actions from the spine creates a bit of a moment or a bit of a leverage system. So a little bit of activity in these muscles has much more influence on the loading of the spine compared to a little activity here. See, you have to pay attention to the distance it is from the spine, and that's what this figure does. As we move through space, it tells us what the instantaneous moment is associated with each muscle. As you could see, we could pick up lots of things here.
Let me end by looking at trunk load here which is the bottom line. We want to know the compressive and sheer forces on the spine, and that's shown here. The yellow is the amount of compressive force where you start to get into problems of micro-fractures which we believe is where you start to have a risk of injury. That would be analogous to the action limit in the NIOSH Lifting Guide. And down is increasing compressive force with the black line here.
So let me just put all these in a window right now, and I'll show you how we typically evaluate a workplace. Typically what we look at are the feature of the box and let the person lift. We could say ah ha. There's a point where he has maximum compression. At that point, he was all right. At this point, he started to get into problems again. At that point, he's all right, and we could see what muscles were working, how fast he's moving, how much load is being supplied to the muscles.
As you probably notice here, lifting straight up and down like this is not what you see in industry. Typically, what you see is the type of environment we showed a little while ago. Let me show you a video of one of those.
Let's look at somebody who's lifting a box out of a slot, and let me pull up the file on that with the data we're interested in and run the model. What we're going to do is look at this fellah as he's pulling a box out of a slot that weighs 40 pounds and simply lifts up like this. Let me just cut to the trunk loading issue here and figure out how much force is on the spine as you're doing this. And so, there we have an analysis of what this job entailed.
He was all right at the beginning of the lift here, and it wasn't until this point right here that he started to load the spine to a point where he could run into problems. That's his maximum moment. So those are the types of issues we're interested in. We've also done some studies of using hoist.
Talk about product design, this will show us with and without using a hoist to do a similar task, and the first thing we'll look at here is the video. This is the activity we're going to be interested in. The person's going to use the hoist and carry it over here. This is an alternative to lifting by hand. We could run the model with that, and we could take a look at what kinds of trunk load we get with that. The person is lifting this thing by hand. You could see, now we're down into the red area here, through a good portion of this lift, it starts right about here. And so, this area here is where you have at least 50 percent of people who have micro-fractures on their spine when they're getting into that point. It occurs right when he starts the lift. We could do a similar analysis as he's using a hoist which is what I just showed you a minute ago.
You should see what this used to be when we had slow computers. I showed you the video of that which is the one we just saw. Trunk load, spinal force. If you remember on the last one we saw, all kinds of activity in the red zone.
Now, we're not even getting into the yellow throughout the lift. So this is the person lifting with a mechanical lifting aid. You can quantify the danger that's imposed on the person as he's working.
Let me show you some of the results of this study. Let me show what we've found in terms of case weight. Basically, what we found is a difference with weight in terms of our risk measures. What we do for industries, we give them a measure like this. We give them a barometer or a thermometer, something they can relate to. Green means you're good. Red means you have a serious problem. Yellow means you have to be concerned about this. So we give them continuum. And so, no matter what measure I use, whether it's our LLM risk model or our compression index, we're going to be able to relate it back to something we could relate to.
Looking in terms of compression, we see increased risks as we increase the weight. But also, look at the range we get in these arrow bars. Something that's 40 pounds could be just as risky as something that's 60 pounds. You could see the same things happen in compression. These are standard deviation bars now. This is where you start to get vertebral micro-fractures. This is where you get a lot of people with them. And still, even the light box has dangerous areas. If you go out three standard evasions, you could see it could be well over the maximum limit.
If we just go to pallet region now, what we see now is we break this down, one box now, one weight of a box, and we just look at whether they're lifting from the top layer, the middle layer, or the bottom layer of the pallet. You could see all the risk is in the bottom layer of the pallet. Top layer, that's fine. Middle layer is fine. As a matter of fact, if we go to the heaviest box there, to the 60 pound box, that's 50. If we go to the next one, you could see that very little of the risk, even with a 60 pound box actually occurs when you have the load high enough. And even the middle level is acceptable. It's not until you reach down to the very bottom of that thing that you really start to have serious compression loads, that could cause a problem. It makes no sense to say, "Well let's leave everything at 40 pounds", because even 40 pounds could be dangerous in the wrong position.
What we saw is that size made a difference but only at the top layer. Who cares about the top layer? That's safe and so, we concluded that it wasn't worth worrying about the size of the box. And now, if we could go to the handles.
This shows what happens with and without handles. You could see handles in a box makes the box look like it's about 10 pounds less. In other words, a 50 pound box with handles looks like a 40 pound box without handles in terms of the compressive load, and you see that relationship all the way up. Here we see the effect of both box weight, where it is on the pallet and factors such as whether or not it has handles. We're able to quantify that and give them the type of information they need. For example, a 40 pound box lifted from the bottom layer with handles puts 3.3 percent of the exertions at risk. Where a 60 pound box lifted from the same layer puts 15.7 percent of the risk in the risk category. Without handles, it jumps up about a third. And so, I don't have time to talk about this in detail, but you could see the benefit here, and we could specifically tell you what the risk is for every single activity that you're doing and tell you where you need to make the changes.
The idea here is how much exposure is too much exposure, and that's what we're able to determine.
What we found in that region was real important. Weight and handle was real important when you considered their interaction with region. So there's more than one way to skin a cat. What that means is you don't always have to reduce the weight on the products that are a problem. What you could do is raise those up to the level that can help.
Lastly, I'd like to show that these same type of measures, can be used in other environments. For example, here's some studies we did in the check stand environment. Look at the effects of check stands. Look at the effects of scanner, similar to what Rob was showing. We're able to tell you exactly what percentage of the motions put a person at risk with different designs of the scanners.
We've done similar things with product design such as spray paint guns. We've done some work with companies that develops those. You can see us analyzing a person spray painting both in terms of muscle activities as well as motion patterns.
Currently, we're doing some studies on keyboards, as is everyone. And we're interested in what are the effects of having these keyboards in all the different orientations, and we've developed monitors such as finger monitors based on fibre optics. That helps us evaluate exactly how people move. So a lot of work is going on in our laboratory these days. I thank you for your attention.
DR. PEACOCK: Thank you very much, Bill.
