Data Schmata

Show me some numbers!

At the end of the last posting the statement was made that it is necessary to address green manufacturing and the role of digital enterprises in the context of informing the customers each enterprise serves as well as those to whom the enterprise appears as the customer. Importantly, this has to be done both external to the organization as well as inside. What does that mean? With apologies to again referring to past postings … this starts with the Google earth view of manufacturing. This was first introduced in a posting way back in 2009. It bears refreshing everyone’s memory! The idea, shown in the image below, envisions one starting at the enterprise level and then zooming in to increasingly detailed parts of the manufacturing enterprise spanning

 "Google-earth" view of manufacturing

the facility, line or system in the facility, the machines in the line, the tooling on the machines and finally the process on the machine. This image is updated from the first one shown back in 2009. Along the left side of the image are characteristics of data flow and operations. For example, data rates and response rates of the elements at the different levels range from weeks and months at the highest level reflecting long term planning to minutes and hours in the line for organization of production to seconds and minutes in terms of the machine functions operation as in “macro planning” and then milliseconds and microseconds at the tooling process levels. These data rates reflect the speed of changes occurring in some aspect of the element that has importance to the overall functioning of that element and, necessarily, the consumption of resources.  The illustration below (from Vijayaraghavan, A. and Dornfeld, D., “Automated Energy Monitoring of Machine Tools,” CIRP Annals, 59, 1, 2010, pp. 21-24) shows this temporal aspect of decisions and impact more clearly.

Required data rates at different levels of the manufacturing enterprise

To affect process control at the process level (here for a metal cutting operation - hence the reference to chips and cutting tool) one needs to have data and response at the micro/millisecond rate. As one moves higher in the structure the timing scale slows down proportionally. When reaching the enterprise level where supply chain management and asset management is of concern the decision and response time is longer. This is not, however, to imply that there are not decisions in supply chain management that do not occur more rapidly in some cases. In fact, the interesting thing about this type of representation is to look for the dependencies at lower levels on decisions and responses at higher levels. For example, a catastrophic tool failure at the process level that causes substantial down time and loss of availability of the machine and line could ripple up to the production planning and scheduling level if the disruption is substantial.

Each interface between the different levels in the manufacturing enterprise, and their accompanying data rates, decision rates and response rates offers an opportunity to add noise to the system (meaning reducing the reliability of the data or, at least, increasing variability in the data) and must be accounted for.

OK … but the Google earth view above has another side to it on the right. In this figure the potential range of influence and impact of the social effects (or dimensions) of the manufacturing enterprise are illustrated. These are challenging to represent in a simple drawing like this but will affect, at the process level in the facility, mostly the workers and support staff (for example, working conditions, safety, training, pay, etc.). The potential range of impact expands as one moves up the levels culminating with the supply chain which can have a national, regional effect or, within that country, a specific community (for example, air quality, water quality, healthcare and education, etc.). The “data rates” for acquiring impacts for these impacts (assuming one can quantify them sufficiently) will be similar as on the “hardware” side although may not be at the fastest level. Monitoring working conditions for exposure to chemicals or other contaminants for the worker at the machine may need to be done on a second or faster rate. Data on health care or educational levels of workers in the supply chain will be less frequent.

Never-the-less, is one desires to apply the digital enterprise concepts to tracking the sustainability of enterprise operations from energy and resources to social concerns the data challenges will be impressive.

We need to get more specific. What will this data look like? To illustrate, three examples are presented her derived from recent research at the Laboratory for Manufacturing and Sustainability (LMAS) at Berkeley. They address a facility level view, a line level view and a machine level view. They all concern manufacturing that centers on production of machinery using a range of processes but with a strong component of machining and metals fabrication. Energy consumption is a common metric here as it is readily measurable.

Facility level - The first example is drawn from the research of Dr. Nancy Diaz (N. Diaz, “Development of Energy Models for Production Processes and Systems to Inform Environmentally-Benign Decision-Making,” Ph.D. Thesis, University of California, Mechanical Engineering, 2013) and focuses on the comparison of electrical energy intensity (kWh/meter squared/year) for four production facilities of a major Japanese machine tool manufacturer. The data reflects the consumption of energy by the machinery in the plant, the heating, ventilation and air conditioning (HVAC) and lighting. The four plants address different parts of machine tool manufacturing from ballscrew production, the most precise (and hence requiring most exacting control of the environment - temperature and humidity) to less demanding machining and assembly. The figure below, from Diaz thesis, illustrates the dramatic range of consumption of energy per unit of floor area for the different factory functions and energy uses. The ball screw production facility has the highest HVAC energy intensity since these are exceptionally precise components that determine the quality and eventual performance of the machine tool and must be produced under the most stringent environmental conditions. Ball screws are turned by the motors on each linear axis of the machine and cause the table on which the workpiece is mounted during machining to move under the control of the computer program. They define the precision and accuracy of the machine movement (to a great extent).

  

Facility level production energy intensity for machine manufacturing

What do we learn from this? First of all, at this level, it is clear what the “relative cost” of different manufacturing processes are in terms of energy (and likely other resources) … precision is the highest due to the requirements of the facility, quality of the consumables, etc. Think of the semiconductor industry as at the high end. Then, it also shows where the greatest potential for improvement is in the process efficiency to reduce this intensity. But, it is also necessary to determine the total impact , meaning, the measured intensity (energy / unit area) times the total area involved in this type of production. If this is a small part of the total production then it might not be the first priority. If it is a major component then it could offer big improvement.

Systems/line level - The second example is drawn from the research of Dr. Stefanie Robinson (S. Robinson, "An Environmental and Economic Trade-Off Analysis of Manufacturing Process Chains to Inform Decision Making for Sustainability," Ph.D. Thesis, University of California, Mechanical Engineering, 2013) and focuses on the energy and resource consumption in a process chain with the objective of establishing a basis for trading off the potential for upgrading specific operations in the line. This was based on research conducted with a major heavy equipment manufacturer in the US. The figure below shows a schematic of a multiple operation process chain and a detail of one of the process operations with typical input and output of energy and other consumables along with waste and emissions.

Process chain and detail of individual process input/output

With a representation of a process chain, and the individual operations, one then needs to determine the consumption and rate of outflow of the major consumables and waste streams. One can appreciate that it is necessary to do a rather detailed analysis of the inputs and outputs (wasted and worn tooling, scrap from production, leakages, etc.) to be accurate. With this data, the actual resource consumption and associated economic and environmental cost can be determined. Then, the impact of changes in any of the production steps can be evaluated both in terms of productivity and quality as well as environmental (energy, global warming, water) effects and associated costs as shown below.
    

 

                        System consumption metrics and environmental and economic "cost"

Process level - This third and last example bores in more finely on the process level detail for a machining operation. Data from this level of analysis would feed into the systems/line level just described. This example also draws on the work of Dr. Nancy Diaz in the above cited thesis. This work developed a  generic method for calculating energy consumption during a realistic machining operation on a precision milling machine based on constant and variable contributions of the material removal rate (MRR). The MRR is a driver of productivity in a machining operation and is based on real time data of the feed rate of the cutting tool, the cutting speed and the depth or width of engagement in the case of milling studied here. This data is now available in real time from the machine controller thanks to standardized interfaces and data formats such as MTConnect and associated software. It is also available from the numerical control program driving the machining operation (that is the path the cutting tool takes in the machining operation) but that is often inaccurate due to actual the performance of the machine in operation. The curve below shows the specific energy (Joules/cubic millimeter, J/mm3) as a function of MRR.

Specific energy consumption for different material removal rates in milling

The significance of this data is that the designer or production engineer can determine the energy to create a part feature from knowledge (either estimated from the tool path or measured in process). And, this was determined for a variety of machining conditions with different tooling - so it has some breadth of application. For other materials, however, the curve would likely shift up (if a more challenging material to machine - more energy per unit of material removed) or down (if easier to machine).

So this is all driven by data! Lot’s of it collected at different speeds and representing different “views” of the enterprise. It is encouraging but humbling. Fortunately, as referred to in the previous blog posting on the digital revolution, communication speeds, computational capability and speed and the hardware spitting out the data from machines and systems are more common, less expensive and more reliable. The expression “drinking from a firehose” comes to mind! 

But, the good news is that no one will be thirsty! Some of the tools for using this data in productive and green operations will be covered in the future.

The Digital Revolution

Dejå vu all over again?!

The last posting started the buildup to using data (from where ever) to drive innovation, clarity and transparency, business model/economics, institutionalization, and benchmarking for industry in general and, ideally, for green manufacturing as well. This data should include information on what any specific process or system is doing, what it is consuming or emitting, what the impact per unit process output is, what is the efficiency of conversion of resources into product, what it the efficiency of the cycle, how does one system or process compare to another doing the same thing, and how does the overall performance match up with competitors in the same market, company, division, or factory, and so on.

The upshot of the discussion is that it should be possible to close gaps between what is needed to understand the items above and what is available. Further, the idea is to leverage the capabilities of big data and the digital views of an enterprise to help close this gap.

First, it is helpful to try to understand what big data and digital enterprises actually mean and then how they relate to our conversation here. A web search for the term “digital enterprise” turns up a lot of product pitches and some useful definitions. For example, WhatIs?TechTarget has a posting which offers the following definition - “A digital enterprise is an organization that uses technology as a competitive advantage in its internal and external operations.”  The “technology” is referring to information technology. This is rather broad. 

Let’s take a look backwards to see what can be learned. In November 1994 Fortune magazine published an article by Gene Belinsky titled “The Digital Factory.” This turned up the other day when I was rummaging through some old files in my office. The article predicts a range of impacts that the digital factory will have from customization of products “literally in quantities of one while churning them out at mass production speeds” to allowing supply chain integration, micro factories and breathing new life into the “beleaguered U.S.  machine-tool industry.” Referring to it as “soft manufacturing” it even proposed that the most astounding effect could be on employment where it “could stabilize or even increase the number of production-worker jobs in the U.S.” The article gives a number of excellent examples where this is being employed circa 1994 and the improvements realized and highlighting that “software is becoming more important than hardware - more important than machine tools - in American factories. And smart humans are back, replacing dumb robots.” It even predicted the importance of 3-D printing for prototyping.

Well, the first part is right … software became more important than machine tools - in the U.S. at least. Since this report the U.S. machine tool industry has essentially collapsed and in its place are builders from Japan and Germany with machines of incredible sophistication. They figured out that software AND the machine tool was a powerful combination. We didn’t. The second part is not. Robots staged a comeback, thanks to capable planning software, better cheaper sensors and efficient motors and controllers combined with a better understanding of where they work best and with what tooling systems. Pick up any trade magazine or “Google” robots and you’ll see an amazing array of co-worker robots doing sophisticated tasks. And productivity in the U.S. is up (see the post in July 2013) but manufacturing employment has not keep up with growth.

Is this current buzz about digital manufacturing just another Fortune 1994 article that, 20 years later, will look equally out of touch? Not likely. The downfall of the last prediction was that as software was growing in importance and capability, the “network” (or what was then connecting things) was infantile compared to what we now enjoy. Ditto for data flow from machines and systems. Sensors on production machinery (not just the position feedback data for machine tool axes or robot arm positions) were expensive, intrusive, slow to respond and often measured things that did not truly reflect the process or element being observed. One could go on at length about this but we’d be way off the path.

Not so now. The examples cited in an earlier posting on the internet of things showed systems communicating an impressive volume of data at high rates - enabling essentially real time behavior and response. The companies that make machinery that link into these systems (the folks that picked up where most U.S. machine builders stopped) learned how to employ the better cheaper sensors and efficient motors and controllers combined with a better understanding of where they work best and with what tooling systems that made robots more pervasive.

So, where does that leave us with respect to greening manufacturing and sustainable production?

Maybe to focus this a bit, let’s go back to the deep well of knowledge provided by McKinsey! In a May 2014 article titled “The Seven Traits of Effective Digital Enterprises,” authored by T. Olanrewaju, he and his colleagues go over examples of “transformational” traits of the successful digital enterprise. These are, in usual McKinsey style, rather high level and inspirational rather than execution oriented. But there are some nuggets of practical ideas - where practical here means “what can we do on the shop floor?”

One is “measure digital value not digital interactions.” This is the digital interactions are “digital-washing” equivalent to "green washing." Results or progress against a benchmark or a fiducial is what counts. But first you need the yardstick.

Another is “don’t accept historical norms; question the status quo; create a plan covering every function, product, business unit and location.” This is none other than the “Google earth view” of manufacturing identifying the elements, interfaces and value at all levels - leave no stone unturned. And, more over, it is looking for effectiveness and not only efficiency. Doing the suboptimal or wrong thing well is not a substitute for doing the correct thing and doing it well (some of this was covered in earlier postings). The last one to note (and please do read the whole article at the link above to get the full story) is “follow the money.” This addresses the “reduced impact for higher value” that has been trumpeted in this blog for some time. But, too often, follow the money is replaced by “follow the energy” and ignores other important consumables - materials, time, water, even labor. Energy is important for sure but many other econsumables are important too - maybe more important in some situations!

The report states “Many organizations focus their digital investments on customer-facing solutions. But they can extract just as much value, if not more, from investing in back-office functions that drive operational efficiencies. A digital transformation is more than just finding new revenue streams; it’s also about creating value by reducing the costs of doing business.”  Wow. We can use that. Do a “search and replace” here for digital investment, back office functions and finding new revenue streams replace them with sustainability initiatives, manufacturing processes and systems and reducing utility bills, respectively. And insert “environmental” between “costs” and “of” in the last line.

Or … following all the substitutions it looks like this. 

Many organizations focus their sustainability initiatives on customer-facing solutions. But they can extract just as much value, if not more, from investing in manufacturing processes and systems that drive operational efficiencies. A digital transformation is more than just reducing utility bills; it’s also about creating value by reducing the costs of doing business. And, digital enterprises should be able to do this better and insure measurable progress.

But there is also a “customer-facing” aspect to this of course. That’s where the circular economy comes in. Every enterprise has customers and is a customer to some other enterprise. That’s what’s shown in the Ricoh Comet Circle and, more abstractly, in the circular economy.

It is necessary to explore this with a circular economy in mind … starting with how to inform the customers our enterprise serves as well as those to whom we appear as the customer. And this has to be done both external to the organization as well as inside. We’ll continue with this in the next posting.
 

Moving to the next level

Or ... Mind the (data) gap

The interest and focus on sustainability is now more evident than ever before. Advertisements in increasing numbers trumpet some aspect of a product or a service as “sustainable”. Usually it is not but that doesn’t stop the attractiveness of using it to sell. Business has also noticed and there is increasing attention to “business plans for sustainability” and evidence that customers, if not investors, reward some businesses for trying to be sustainable. But, as mentioned last time, to is not clear if we are making any real progress.

Some attribute this to the presence of a “green gap.” The opening statement in a report from 2011 by Ogilvy and Mather sums up the “green gap” as follows:

“While we have been relatively good at getting people to believe in the importance of more sustainable behaviors, practices, and purchases, we have been unable to convert this belief fully into action” (p. 13).

For reference, the “green gap” is defined in the report as the gap between consumers’ green intentions and green actions. One might argue that this applies to business, and manufacturing, as well.

This is the other end of the equation with respect to increasing value while reducing impact (as it defines what consumers are willing to count as “value” in the domain of sustainable products) and it provides animation for implementing the circular economy. If there is no motivation or perceived reward and the value is not recognized then circular concepts, unless masked in conventional marketing or product functionality/value, will not be successful.

There was frustration expressed at the meeting held as part of the process to generate this report that, while many people in leadership positions - the so-called “thought leaders” - keep hammering away on the issues and need for action, the mainstream consumer is not really responding. Or, if responding, not responding rapidly or massively enough.

The chart below illustrates this point. In a survey of behavior in the US and China (PRC) respondents were asked indicate the importance of certain activities in terms of their definition of living a green or sustainable lifestyle (called “importance”). The then were then asked with respect to these activities whether or not they usually do the activity (called “behavior”). The gap between the two responses shows the divide between belief and action ... the “green gap.” The activities asked about were:  

- taking public transportation,
- walking or biking to work
- purchasing locally grown food
- using eco-friendly cleaning products
- recycling bottles/cans/paper.

These are not, granted, the whole set of behaviors defining a green lifestyle or preferences (nothing about water, or reusing products, etc.) but are a reasonable set of trade-offs. And, of course, they are life style preferences and not directly related to production of goods and services.

China and the US were selected due to the impressive contributions to global warming of their economies.

The report mentions the desire of major corporations to assume more leadership in developing practices and products that address climate change, for example, but also the realization that in many cases the biggest impact of the product is in the use phase and not in the production or manufacturing phase. This has been discussed extensively in the past in this blog.

The suggestion was that rather than trying to get every one motivated to follow a better course on might need to talk to a larger audience than just the “committed greens” who already get it. Oglivy called this larger audience the “massive Middle!” This is not to be confused with the ‘silent majority’ of the Nixon-era (Google it if you don’t follow!) Ogilvy focuses on consumer issues, and angst about contrasting desires with needs, but  also gives a set of 12 ways to close the gap. Some of these have great applicability to business in general and manufacturing in specific. The objective is to “make green mainstream.”  

The 12 ways Ogilvy lists (with my translation to manufacturing space) are :

1) make it normal; in industry speak, institutionalize green behavior and practices.

2) make it personal; Oglivy intended this to be linking products to individual behavior; for manufacturing this is getting everyone in the enterprise connected to the activity.

3) create better defaults; in manufacturing this would be to have a series of options so that the fall back is not business as usual but another green alternative.

4) eliminate the sustainability tax; Oglivy relates this to the usually higher cost of green product; the manufacturing analogy is to insure that the economics are sound and there is a solid business model for this way of operating.

5) bribe shamelessly; this is not your usual bribe to get around regulations or influence decisions! This is rewarding products and services for behavior; in the manufacturing world, this means recognizing leaders, and their products and technologies.

6) punish wisely; shaming people into good behavior has some benefits if applied carefully they argue; in manufacturing, this is likely best done by benchmarking and providing metrics so that the organization can see where it is and where it needs to go. The days of “the flogging will continue ’til moral improves” are over!

7) keep innovating; this is easily translatable to manufacturing; in fact, sustainability drives innovation in manufacturing.

8) lose the crunch; Ogilvy is referring here to the image of green as Birkenstock wearing granola munchers (hence the “crunch”!) … which is not really an issue in Berkeley! It really means making green more mainstream; For manufacturing that is what this blog is all about.

9) turn eco-friendly into male ego friendly; This is Oglivy’s way of making green less “girly green” (their words … not mine!); This does not really relate to manufacturing as, for example, green machine tools are not considered less manly than conventional ones.

10) make it tangible; convert the tangible benefits of sustainable to something that can be easily visualized; manufacturing is attempting to do this all the time - from a cost, performance, impact, efficiency or effectiveness aspect.

11) make it easy to navigate; truth and transparency … easy to follow the dots; this maps directly to manufacturing and can relate to "eco-roadmaps" and similar to be discussed more in future postings.

12) tap into hedonism over altruism; help consumers see the fun on the green side of life; not sure how we can relate this; manufacturing is to many of us “fun” already - so one can suppose that green manufacturing can be “more fun”?! Let’s not push this one too far.

So now you are probably asking, how do we connect this back to big data?!  If one follows the above discussion about the key steps to address this massive middle as it relates to manufacturing, one can look at the ways outlined above and see some common elements
needed to enable these for manufacturing - all dependent on information.

The innovation, clarity and transparency, business model/economics, institutionalization, benchmarking, etc. are all driven by data. Data on what your process or system is doing, what it is consuming or emitting, what the impact per unit process output is, what is the efficiency of conversion of resources into product, what it the efficiency of my cycle, how does one system or process compare to another doing the same thing, how does my performance match up to my competitors in the same market, company, division, or factory, and so on. All determined by data. And data flowing from machines, systems, facilities and enterprises.

So we can close this gap, at least as it relates to green manufacturing, by leveraging the tools and capabilities of big data and the a digital view of our enterprise. This is where the story picks up next time with more details and some examples.

Circular economy, II

Progress and big data

At the end of the last posting the question was posed “can the “internet of things” be part of the circular economy? Can this connectedness push consumers to consider more sustainable behavior, or create products that provide increased value with lower impact, or allow effective recovery of resources at end of life?” The answer proposed was the very definitive “it depends”! Which is true - depends on reaction (or pro-action) of consumers, depends on reaction (or pro-action) of companies, and depends on reaction (or pro-action) of governments and non-governmental organizations (NGO’s).

In attempting to insure products and services in the manufacturing sector that reduce impact per unit of value created we’ll need to be careful in accounting for all the impacts generated and environmental return on  investment.

That means data … and metrics. Good data (not just streams of “information”) and real metrics that relate the engineering and manufacturing efforts with machine, system, enterprise and product performance.

This starts at how we measure growth in the economy. If we do not consider the impact of growth, broadly speaking, then the growth is pushed without consideration of the collateral issues - energy, water, materials consumption and the relevant impacts as well as the important social impacts across the supply chain.

A recent article posted on the Aljazeera America site, written by Sean McElwee, makes the point well. The article, titled “Gross Domestic Problem” (after GDP more traditionally meaning gross domestic product), states that “GDP is a fine measure of the goods and services produced within a country’s borders. However, it does not tell us how sustainable that growth is or at what cost it comes.” The sustainable part here refers to the business sense … will it keep going. It is the last bit “… at what cost it comes” that should interest us. They author refers to a paper in the January issue of Nature by a group of social scientists who argue that “If a business used GDP-style accounting, it would aim to maximize gross revenue — even at the expense of profitability, efficiency, sustainability or flexibility.” And this time they mean the real sustainability!

The Nature article states that the gross domestic product is a misleading measure of national success! They cite Robert F. Kennedy’s observation that the country’s GDP “measures “everything except that which makes life worthwhile.”  And the result is … while world GDP has made impressive gains since it was introduced around 1950 “progress” defined broadly may not be so impressive.

The problem is seen in the graph below, showing growth in GDP over the last 5 decades and the comparable growth in GPI (so-called genuine progress indicator). The Nature article explains that the the GPI is calculated by “starting with personal consumption expenditures, a measure of all spending by individuals and a major component of GDP, and making more than 20 additions and subtractions to account for factors such as the value of volunteer work and the costs of divorce, crime and pollution.” Meaning, it can include the impacts of “progress” such as destroying wetlands or depleted water resources.)
 

Figure: GPI and GDP over time (source: Kubiszewski, I. et al. Ecol. Econ. 93, 57–68 (2013).)

If you believe the GPI metric - one can see that sustainable progress is not progressing!

And corporations that follow the piper of growth without accounting for well-being because it is what the accounting systems and shareholders expect are just doing good business.

And countries that try to increase GDP/capita because that is associated with affluence (recall the IPAT equation?) and everyone wants to be more affluent.

That’s why Patagonia founder Yvon Chouinard cited in the last posting was so upset with corporations and “business as usual” … no one wants to restrict growth.

The Aljazeera article sums it up nicely. “GDP doesn’t even include the price of everything. For instance, the International Monetary Fund found that our failure to price the effects of carbon dioxide amounts to a $1 trillion annual subsidy for fossil fuel corporations. Conversely, the Clean Air Act produced $22 trillion in economic benefits from 1970 to 1990, according to an EPA retrospective study — much more than the estimated $523 billion it cost. In each case, GDP ignores crucial public benefits and the externalities of economic growth.”

As a result, Aljazeera notes from a landmark study titled “Mismeasuring our Lives”, “what we measure affects what we do, and if our measurements are flawed, decisions may be distorted.” So, making a choice between promoting growth as measured by GDP and protecting the environment may be false choices if the environmental degradation can be calculated and appropriately included in measurements of economic performance. 

I hope Mr. Chouinard read this! Actually, he would hope more corporate CEO’s read this!

But, this posting is not just ranting about the inequities created by a GDP centric view of the economy … what’s the solution and how does manufacturing fit in .. or, at least, big data, help.

Interestingly, this problem (coming up with the right way to measure things so the true impact or benefit or cost can be determined) is something engineers, specially manufacturing engineers, have been dealing with for a long time. In the field of manufacturing we often quote Lord Kelvin (aka Sir William Thomson) who stated “To measure is to know" and following on “If you can not measure it, you can not improve it." In lay terms, if you can’t measure what you made you don’t know whether or not you made it! Seems time to extend to this to measuring real growth on the way to sustainable development.

And that is where big data (or any data!) comes in! The circular economy, using resources effectively and efficiently - let’s say productively - will rely on the linking of a host of consumers all along the supply chain (from material sources to converters to manufacturers to distributers to consumers and back - recall the Ricoh comet circle).

According to McKinsey (the “Wikipedia of the Fortune 500 set”), in manufacturing big data can be useful for identifying ways to increase yield in a number of processing operations by identifying “insights” into production that were overlooked due to complexity of the process, large numbers of variables, many differing process stages, etc. If this same ability to uncover “insights” could extend to the broader impacts of manufacturing across the supply chain that would give both a sound technical basis as well as a reliable economic measure of the value of improvements.

This gets us back to the one element of the IPAT equation we can actually influence - Impact/GDP. That is, increasing the value created to the consumer or the market with reduced impact measured however you think is important (recall we indicated this would have to be on the order of 10X reduction to offset increased population and demand).

Maybe the real ratio we should be concerned with is GDI/GDP! Genuine progress per unit of GDP growth. If we have (or can get) the data for our manufacturing enterprises to determine with sufficient accuracy the impact on GDI of our production and our products this might give us a basis for making decisions.

Then, we could move beyond eco-charts plotting reduced environmental damage vs economic benefit where we assume a 1:1 relationship is sufficient to a plot of GDI vs GDP (on a local scale of course) to evaluate our decisions from design to production.

This will be challenging. It will have to be “circular” as we cannot gain the resource productivity that drives this any other way.

We’ll need to work on more details in future postings!

The internet of (green) things

Or … what would my refrigerator tell me if it could talk?

Recently I was at a conference on manufacturing where I was caught in in an avalanche of buzzwords … cloud, big data, internet of things, industrial internet, connectivity, connected revolution and so on. This feeding frenzy of connectivity and data is driven by a number of things, real and imagined. Businesses see opportunity for enhanced productivity and reduced time from design to production. Other businesses see opportunities for providing services and products to an informed customer - all at much greater speed. Others still see a chance to offer analysis capabilities to convert the “firehose stream of data” to a manageable set of results and metrics.

For example, in the manufacturing domain, General Electric is driving the creation of an “industrial internet” which GE expects will define how “industrial equipment with sophisticated sensors will be linked over a network that connects people to machines and machines to one another to boost efficiency.” They won’t be taking to refrigerators, at first, but jet engines to indicate potential maintenance requirement or, closer to the factory, failure potential and maintenance needs of sensor-enabled machinery on the factory floor.

In the manufacturing space. a leading commercial computer aided manufacturing (CAM) software provider, DP Technology/ESPRIT, has introduced a cloud-enabled tool path planning capability  - cloud-enabled CAM. The ESPRIT MachiningCloud Connection gives programmers (the smart folks that create the instructions and select the tooling to allow sophisticated numerically controlled machine tools to create the complex physical components that make up manufactured products) access to complete and up-to-date tooling product data, cutting hours of programming time by eliminating manual tool creation. This would have been done with physical paper catalogs of tools, configurations, cutting inserts, and other peripheral hardware to make it work (think of shopping at Sears or Target before websites, online catalogs or Amazon! If you are old enough to recall Sear’s paper catalog which was like a phone book for a large city, if you are old enough to remember phone books too, it is an interesting but long and manual process!). This capability simplifies the selection of cutting tools and, better yet,  offers a list of recommended cutting tools based on machining features and machining sequences that are planned. Finally, the programmer or manufacturing engineer can simulate the machine operation and behavior with accurate 3D models of tool components and assemblies.

In the design and collaboration space, Autodesk has introduced Autodesk 360 for design innovation and collaboration.  More than just two dimensional “drafting,” this cloud-based tool that provides free online data storage and a powerful, secure set of tools that improves the way engineers and others can design, visualize, and simulate anywhere and with “virtually infinite computing power”. This also simplifies collaboration among co-designers and customers, and streamlines workflows.

And then, of course, things that talk to you. Top of this list is probably the Nest thermostat recently acquired by Google, Inc. By use of training cycles, and observing your “behavior,” it learns what temperatures you like and builds a personalized schedule. Nest says if one teaches it efficient temperatures for a few days within a week, the thermostat will start setting temperature schedules on its own. And, with the Nest app you can connect to the thermostat from a smartphone and, if arriving home early (or later) change the temperature miles from home.

So what is the internet of things anyway? My favorite first “go to” source is a Google search which, usually, gets a Wikipedia hit right off … for “internet of things” Wikipedia defines the term (and acronym IoT) as referring to “uniquely identifiable objects and their virtual representations in an Internet-like structure.“  Apparently this term has been in discussion since the early ‘90s and was formally proposed by Kevin Ashton in 1999 (Ashton, Kevin, "That 'Internet of Things' Thing, in the real world things matter more than ideas," RFID Journal, 22 June 2009.) though the concept has been discussed since at least 1991. Wikipedia goes on to explain that In 1994, the Internet of Things was known as “control networks,” which Reza Raji discussed in an IEEE Spectrum article as “[moving] small packets of data to a large set of nodes, so as to integrate and automate everything from home appliances to entire factories.”

Home appliances to entire factories! All communicating with other devices, computers and, presumably, people.

But what might the effect of this integration and resulting actions be? Better productivity? Increased consumption? Smart consumption? Smart and sustainable consumption? It depends.

Capitalizing on this drive to connectivity Amazon has recently introduced their own “smart phone." The New York Times article characterizes this as “a device that tries to fulfill the retailer’s dream of being integrated into consumers’ lives at every possible waking moment — whether they are deciding where to eat, realizing they need more toilet paper or intrigued by a snatch of overheard music.” Meaning … sell, sell, sell!

So, are we making progress or not? A quote from Patagonia founder Yvon Chouinard in a conversation to an audience of hundreds of CSR officers and aspiring eco-preneurs may offer some insight. He said “If these Fortune 500 companies are now cleaning up their act, then why is the world still going to hell?” “The elephant in the room is growth: you make an energy-efficient refrigerator, so then you buy two of them. Not one public company will voluntarily restrict growth to save the planet.”  Well … that does not sound very encouraging.

So, back to the discussion about the circular economy.

Can the “internet of things” be part of the circular economy? Can this connectedness push consumers to consider more sustainable behavior, or create products that provide increased value with lower impact, or allow effective recovery of resources at end of life?

First reaction is, again,  … it depends!  If this pushes consumers to by more “impactful” products because they are or can be connected but don’t offer proportionally increased value … then this is not a good sign and Yvon Chouinard will cry foul! If the connectedness can drive a reduction in impact (due to better efficiency, or more effectiveness, consumption only when in use and at reduced rates of consumption, for example) then probably yes. Meaning, if it can affect consumer behavior in a positive direction then this is worth exploring.

This difference between consumer actions and consumer wishes for sustainable consumption is commonly referred to as the “green gap”. We’ll discuss this more in future postings.

So we will need to be careful about tracking the cost-benefit or, at least, providing some feedback to the consumer on the performance of the product or, sadly, this will simply be another round of technology driving increased consumption. And that’s not circular.

We’ll continue with the Circular Economy, Part 2 in the next blog - which will follow sooner than this one did to the last posting (!).

Creating the Circular Economy, Part I

Or putting some wheels on the Ricoh comet circle

The end of the last posting (an embarrassing long time ago!) spoke of the need to do a better job of communicating just what sustainability is. That is, of course, one of the objectives of this blog - or at least as it applies to manufacturing, design and all things related to product creation and production.

An early concept introduced way back in September 2009 was the circular nature of sustainability as practiced in society represented by the Ricoh Comet Circle reproduced here below.

The circle diagram visualizes nested loops of tight or loose linkage between the consumer and the forward and reverse supply chain. The forward loop is from material extraction through production to delivery and use. The reverse loop (at the bottom of the comet) is after the consumer is done with the product and winds back through recycling, recovery, and return to material supply chain. Usually when a green supply chain is mentioned it is in the context of the return loop - resource recovery. That is only half the battle and, if the forward loop is done correctly, is much easier.

The nested loops start with the consumer as “the comet’s core” and can be you or me at home, or a company buying something (machinery, paper, electronic components) and the loops represent “the comet’s tail”. A key idea of the comet circle is that the closer to the consumer that the circle loops … the more sustainable/green is the scenario.

I use this image in my sustainable manufacturing class as well as in other presentations to illustrate the circularity concept of material/product use and reuse as higher valued than destruction and disposal.

As part of the earlier blog posting about the comet circle the strategy behind the creation of the circle was summarized from Ricoh as:

 1) including the identification and reduction of environmental impact at all stages (Japanese continuous improvement at its best and key to identifying elements of the operation that need to be identified, quantified, and reduced, eliminated or otherwise offset).

This places priority on "inner loop" recycling (the highest value resources are those either returned, after repair/upgrade, to the consumer or converted into product and used by their customers along with  minimizing the resources, cost, energy needed to return a used product to "the state of highest economic value.”

 2) institute a multi-tiered recycling program (reduce the consumption of new resources and generation of waste)

 3) create a more economically rational recycling system. This is important and is part of establishing the business motivation for green manufacturing, including the original production stages in the equation. That is, the "green supply chain," and

4) establishing a partnership at every stage of the supply chain. This partnership discloses materials used in production and in the product, transportation alternatives, etc.

To quote from Ricoh on the logic represented here - ”A sustainable society must also establish a recycling system in which products and money flow in opposite directions in both post-product-use stages and original production and marketing stages." At the same time, it is important to establish a social system that helps people to be aware of environmentally-friendly business activities and buy products with less environmental impact.

Flows of money and products at both the incoming side and the outgoing side of product use and social systems that influence customers awareness and buying preferences - that's novel and the combination drives business strategy.

More recently this concept is referred to (or at last popularized) as the “circular economy.” I am not sure which came first. The easy source of all information (buyer beware) - Wikipedia - indicates that it might trace to a book by Walter R. Stahel and  Geneviève Reday-Mulvey in 1981 titled “Jobs for Tomorrow, the potential for substituting manpower for energy” and published by Vantage Press, New York, N.Y. The book was based on a report for the European Commission on the potential for the service-life extension of goods as a sustainable strategy to create jobs, save energy (and GHG emissions) and prevent waste. The micro and macro level analysis was done to two sectors, automobiles and buildings, in France. There is more history on this on the Product-Life.org website under circular economy.

Stahel’s work generally proposed four major goals: product-life extension, long-life goods, reconditioning activities and waste prevention. It also promoted the importance of selling services rather that products when possible. There will be more on this early work in following postings.

The Ricoh Comet Circle was likely motivated by this. And, of course, the “Cradle to Cradle” book by Braungart and McDonough is an outgrowth of this thinking as well.

But there is more history to this!

The concept of “full circles” animates many early philosophical and religious thinking. I heard an individual recently at a meeting refer to the Hindu teachings of full circle or full cycle (Saṃsāra) and the repeating cycles of birth, life and death (reincarnation) goes a long way back.

More recently, the  Ellen Macarthur Foundation and, McKinsey building on the Macarthur Foundation work, have been detailing business aspects of implementing the circular economy. The thesis is to move away from the “take, make, dispose” system and replacing it with restoration.

The image below, from a McKinsey Quarterly Report, No. 1, 2014 titled “Shaping the Future of Manufacturing” as part of a section on “Remaking the industrial economy”  illustrates how, in a circular economy, products are designed to enable “cycles of disassembly and reuse” and thus reducing or eliminating waste. You may want to click on the image to get a larger view.

There is a comparison between these cycles in biological-based materials on the left of the illustration and “technical materials” on the right side. At the bottom of the illustration are notes about minimizing “leakage” - the loss of opportunities to re-use materials before returning to soil for biological materials and landfilled/burned for technical materials.

The loops in the illustration (for example, on the technical material side, of maintenance, re-use/redistribute, refurbish/remanufacture, etc.) mimic the loops in the comet circle.

As with green manufacturing, this is a concept that is logical and possible to illustrate schematically but can be challenging to actually implement in practice - that is, to put some wheels on the concept so we can move with it! 

We’ll do more with this in the next posting - Part II of Creating the Circular Economy.

New Year's Resolutions

or ... Things that renew our faith in the future!

Over the New Year in the US (perhaps other places too) there is a tradition of making a set of “resolutions” or pronouncements and promises that one will follow in the upcoming year that will make things better. These often have to do with personal behavior (“I will try to like my co-workers”) or health (“I will work out more and eat less”) or finance (“I will try to live within my budget”) and so on. Typically these last a few weeks or months before the reality of daily life kicks in and they are forgotten. But, no worries, another new year is just around the corner.

In thinking about new year’s resolutions this time around and this first posting of the new year it seemed worth while to cite a few things that, relative to green and sustainable topics, encourage one to try to stick to at least an effort to become more sustainable.

So, I took a survey of what I had seen recently that made me encouraged. These are, in no particular order, reviewed below. The continuation of the discussion in the last posting on increasing the effective utilization of resources will come up in the next posting. But … these bright spots below certainly encourage an atmosphere that lends itself to better resource productivity.

First of all from my student researchers. We had a retreat in our lab back in November and we posed the question “What would a sustainable world look like? This came as a result of a provocative question posed to the audience at the Verve conference in San Francisco this Fall by Paul Hawken. He mused that maybe we should start concentrating on what a sustainable world embodied rather than just increasingly long lists of what is not sustainable about the world. This made good sense - sometimes the easiest way to identify the way forward is to reverse the way back!

So, in response to the above question about how the world would look if it was sustainable, the following responses, prefaced by “I know the world is sustainable because …” were noted:

- I am able to achieve my aspirations without limit
- I can meet my needs without “excess consumption”
- I have access to enough information to make truly informed decisions about consumption
- as an engineer, I can clearly see the connection between design, manufacturing, and impacts
- where to the extent possible, all output of activity or consumption is reused efficiently in the creation of new products, new energy, new capabilities, and
- I have the optimal level of control over my environment and products. I am able to use information to adapt to my environment. I live in a smart environment that adapts to my needs (e.g. NEST thermostat).

Not bad … and, as engineers, lot’s to work on there both for consumption and provision of goods (as manufacturers).

Encouraging for sure. There was more discussion which will come up in our continuing discussion about resource productivity. And, the grad course in Sustainable Manufacturing is taught at Cal again this spring so this list will be expanded thanks to input from a larger group of students.

Second, the McKinsey Global Institute publishes reports from time to on strategic observations, insights and trends in business and the world. These are invaluable both for their content and for the obvious expense that went into them (McKinsey is not cheap!). In July 2013 they published a report titled “Game changers: Five opportunities for US growth and renewal.” Granted, this is US centric but the potential, given the prominent role of the US economy is impressive. 

So, what are these five and what does it have to do with sustainable manufacturing? They are:
    - Energy: Capturing the shale opportunity
    - Trade: Increasing US competitiveness in knowledge-intensive industries 
    - Big data: Harnessing digital information to raise productivity
    - Infrastructure: Building a foundation for long‑term growth
    - Talent: Investing in America’s human capital

I will not comment on the first one as the issues of “bang for the buck” in terms of the environment are still being resolved. It clearly however offers a great source of energy close to us and not affected by global politics (the current debate in the US Congress not withstanding!).

The McKinsey report says that these five are all on this list because the technology breakthroughs underpinning these couple with the “changing costs of capital, labor, and energy around the world; policy innovation at the state and local levels; or new evidence-based understanding of how to address long-standing problems.” They go on to explain that, specifically, “… the shale boom, for example, is boosting trade competitiveness, particularly in energy-intensive manufacturing, as the shift in input costs caused by cheap natural gas has made the United States a more attractive place to base production. Big data can play a role in raising the productivity of knowledge-intensive manufacturing for export, maximizing infrastructure assets, and facilitating new personalized digital learning tools.” Addressing education and workforce training,  a “talent revolution” will be needed to train tomorrow’s energy engineers and big data analysts, as well as the skilled workforce needed for a 21st-century knowledge economy.” One result is “longer-term enabling effects that build competitiveness and productivity well beyond 2020.”

The impact in productivity and efficient use of resources is what should intrigue us. The use of  big data analytics in manufacturing and across production processes and systems and product design offers many opportunities for progress. Engineers can link computer-aided design with data from production systems to minimize production costs and raw material use (increased yield!). During production, sensors in equipment can feedback information to minimize disruptions by monitoring operations for breakdowns and wear and, then, signal for preventive maintenance. Finally,  the use advanced simulation techniques to create 3D models of new processes and factories (and the resources they consume) can make green manufacturing embedded in industry. With enough impact industry can become sustainable. 

This will require some "readjustment" in the way we develop the workforce to support this new way of operation - but that is for another discussion.

Third, and this is heartening, a recent comment published in Nature by Robert Costanza and colleagues  (Vol 505, 16 January 2014, p. 283) made the bold statement “Time to leave GDP behind” (!). The authors note that “When GDP was instituted seven decades ago, it was a relevant signpost of progress: increased economic activity was credited with providing employment, income and amenities to reduce social conflict and prevent another world war. But the world today is very different from the one faced by the global leaders who met to plan the post-war economy in 1944  … The emphasis on GDP in developed countries now fuels social and environmental instability. It also blinds developing countries to possibilities for more-sustainable models of development.” Yes! 

This is a must read! Those of us working to build sustainable manufacturing systems … in support a sustainable world … can only gain when the terms are clear, the metrics are logical and well defined and the impacts of our actions “fit” the environment we are working in.

Finally, speaking of “terms”, GreenBiz.com had a short piece by Anna Clark posted on  January 15, 2014 titled “Should 'sustainability' still be a buzzword in 2014”? Many don’t think it should ever have become a buzzword ... but stuff happens. 

And this question, of course, is posed by some of the same folks whose coverage has made the word overused and, sometimes unfortunately, linked to things or actions that are marginally sustainable or, at best, green. In fact, the first line of this short piece reads “Every New Year brings fresh jargon to the sustainability field. The practice of coining new phrases can breathe vitality into old ideas, but marketers also can overuse the tactic in their quest to sell books and training seminars. (I am guilty, too.)” She admits that our goal is a sustainable economy but the word sustainable is poorly defined and “squishy”. Her new year’s resolution is to “do a better job at communicating sustainability. Not just the concept, but also the word.” Yes!

That’s what we aim to do too! So, that’s one resolution I can keep.

More next time.