Effective Utilization of Resources
As part of thinking about mechanisms and metrics, for driving green manufacturing, it came to mind that there is always a lot of talk, specially in the US, about the tremendous advances in labor productivity that have occurred over the last several decades. The Bureau of Labor Statistics (or BLS) is the official keeper and generator of this statistic about the performance of the US economy.
The BLS website defines labor productivity as the relationship of “output to the labor hours used in the production of that output.” It measures these in terms of two productivity metrics – major sector and industry productivity. BLS states that “The Major Sector Productivity program publishes quarterly and annual measures of output per hour and unit labor costs for the US business, non-farm business, and manufacturing sectors. These are the productivity statistics most often cited by the national media. The Industry Productivity program publishes annual measures of output per hour and unit labor costs for US industries.”
The kind of “news” this generates is typical of the following, from the BLS website, reported on June 5, 2013. “Productivity increased 0.5 percent in the non-farm business sector in the first quarter of 2013; unit labor costs decreased 4.3 percent (seasonally adjusted annual rates). In manufacturing, productivity increased 3.5 percent and unit labor costs decreased 10.0 percent.”
This means that, thanks to a number of improvements in industry, manufacturers managed to squeeze out 3.5 percent more output per unit of labor input. This could be due to work organization, automation, simplified production, incentives, etc. This is generally considered to be “good news.”
In fact, the increase of productivity in the US labor market is a driver for business competitiveness. Higher productivity maintains a strong labor-cost advantage (at present, US productivity is 3x Mexico, for example) and has been growing at about 2.5% each year.
So, what does all this have to do with green and sustainable manufacturing!?
Why not measure and track resource productivity too?
Seems obvious when you think about it. Why not consider resource productivity along with labor productivity as a measure of competitiveness for manufacturing (or any industrial sector for that matter)?
Gary Pisano and Willy Shih in their book “Producing Prosperity – Why America Needs a Manufacturing Renaissance,” Harvard Business Review Press, Boston, 2012, discuss productivity as a measure of innovation in manufacturing. They refer to something called “Total Factor Productivity” which combines all inputs – labor, capital, and others – to create a measure of overall efficiency for an economy. This is driven by innovation in products and processes and makes a company, country, region attractive to productive activities. (Note: this is a good read if you are thinking about broader manufacturing issues and not “just” green manufacturing!)
So, how does this fit in?
Recall the IPAT impact equation? Its been discussed a number of times in this blog (most recently back in May) and it proposes a simple methodology for assessing the impact of technology (and manufacturing of products) based on the population, a measure of affluence or standard of living (here the GDP/capita – an imperfect but useful metric) and the impact per unit of value created in manufacturing (impact/unit GDP).
You may remember that I made some note that the only thing manufacturing engineers can affect in this equation to move towards reducing impact is the impact/unit GDP – that is, the impact (in terms of consumption or generation of damage) of the products we create. If we can offer the same or greater value with reduced impact we are on the right path.
So, sounds a lot like productivity doesn’t it?
The problem is, we’ve got to get moving.
At present our impacts are too large. According to Dr. Margot Hutchins, the Associate Director of the Laboratory for Manufacturing and Sustainabiity (LMAS) at UC-Berkeley, we are utilizing 1.5 times the capacity of the planet in terms of resource consumption with an impact of emissions of CO2 and pollutants, depletion of resources, solid waste, etc. The usual problems.
Looking to the future she predicts that population (the P in IPAT) will will increase by ~40-30% by 2050. Affluence, A in IPAT, is also growing quickly in many nations – ~3-5x increase by 2050. And this is to be expected. Everyone wants a better standard of living. The result is that we may need to increase our efficiency (that is, reduce the T) by a factor of nearly 10!!! Meaning, we’ve got to reduce impact of our products while maintaining their value – or growing it – in the eyes of the consumer.
Tall order. So, how would resource productivity come into this?
First of all, how should we define this? Following on the definition of labor productivity, resource productivity would be the amount of output (value) created per unit of resource expended (or unit of impact).
How might we measure this? These units of resource (or impact) could be employed – – Global warming gases emission (CO2, methane CH4, N2O, CFC’s) – Yield or % Recyclability – % Reuse of materials or remanufacturing – Pollution (air, water, land)
and these could be per capita, per GDP, per area/nation, and so on.
As with higher labor productivity which bolsters a nation’s labor-cost advantage, higher resource productivity maintains a strong resource-cost advantage.
More value, lower impact – sounds like something we should look into.
It is sort of like the term used in the aerospace industry – the “buy to fly ratio.” This term came up in this blog back in July of 2010 as part of a discussion on Degrees of Perfection. It is, in a nutshell, the amount of material, for example, that ends up flying on the aircraft normalized by the amount that was purchased and processed at the start of the production line. It is often, for some aerospace components, a very low number.
But we also see this in other products. You may recall a conversation on this back in June of 2011 under the topic of Less can be more based on some research by Professor Julian Allwood at Cambridge University on the yield of material in processing to create some common products – like beverage cans, automotive panels, etc. But Professor Allwood is more careful in his counting. He doesn’t just track yield gate to gate in part of the production but all the way from the melt on creation to the finished product. In the case of both steel and aluminum the “cumulative yield” (meaning the amount of material from the raw stock – in this case liquid metal in the ladle after it was refined – to the finished product) was as low as 40-50% in some cases and, for some aerospace components fabricated of aluminum, in the low ‘teens.
And the “cumulative impact” of that material when it finally got into a product necessarily included the energy that processed the “wasted” material along the path to production. Just because you recycle material that is left on the shop floor doesn’t mean you “hit the reset button” on imbedded energy, or its environmental impact, in the product.
This did not mean that the manufacturers were being necessarily wasteful – just that the process technology was not able to extract more finished product out of the material without large amounts of waste.
This is not usually accounted for (except in the price of the component which reflects the material and processing supply chain). But the associated impacts for sure aren’t accounted for.
What if we were measuring, along with labor productivity, the resource productivity? Would this drive us to innovate in the process technology to improve the “buy to fly ratio”? It would reduce the impact in proportion to the increase in yield of material processed – less waste means, in addition to less cost, less impact. Each kg of wasted material has embedded energy, water, and other resources in it.
Let’s start talking about resource productivity when we speak of manufacturing. And this can be a strong driver for manufacturing innovation as well.
In my next articles, I’ll address some of the follow-on innovation that could improve our resource productivity and, in the process, explore some ideas on tracking resource productivity.
David Dornfeld is the Will C. Hall Family Chair in Engineering in Mechanical Engineering at University of California Berkeley. He leads the Laboratory for Manufacturing and Sustainability (LMAS), and he writes the Green Manufacturing blog. This article was republished with permission by David Dornfeld.
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