Jane M Fraser

Source: Wikimedia. This image is in the public domain.

An illustration of a mathematical optimization problem with two decision variables (shown on the horizontal and vertical axes), three constraints (shown in black, teal, and purple), and a linear objective function (shown in red) that is to be maximized. The optimal solution is 130 for the variable on the horizontal axis and 20 for the variable on the vertical axis; that solution yields a value of 49,000 for the objective function.

What’s new?

As reported by Nature and phys.org, the 2021 Abel prize was awarded to mathematicians László Lovász and Avi Wigderson for their work on computational complexity.

What does it mean?

If, like me, you enjoy putting together jigsaw puzzles, you know that every puzzle is labeled with an important number: the number of pieces. That number is a fairly good predictor of how much time it will take you to put together the puzzle. Once the puzzle is done, you know you have solved it correctly simply by seeing that the resulting picture is complete. You have found the unique, best solution.

Much of what computers do takes the form of solving mathematical puzzles: finding the best route for a delivery van, assigning flight crew members to flights in the best way, assigning jobs to machines in a production facility, deciding on the best way to cut a tree trunk into lumber, and so forth. For many mathematical puzzles, like the jigsaw puzzle, the size of the puzzle is a fairly good predictor of how long the puzzle will take to solve, and for some – but not all such mathematical puzzles – when you have found the best answer, you can easily confirm that the answer is the best.

The field that deals with solving mathematical puzzles like these is called optimization (notice the use of the word “best” in each of the stated puzzles above) and the field that studies the difficulty of such puzzles (how long will the puzzle take to solve) is called computational complexity.

In optimization, the puzzles we solve are expressed in mathematical form. We want to select values of decision variables to maximize or minimize an objective function (expressed as a function of the decision variables) while meeting all of the constraints of the problem (expressed as inequalities or equations, again as functions of the decision variables). In my June 27, 2020, blog on operations research I wrote about linear programming as an example, where the objective function and constraints are all linear functions of the decision variables, but other puzzles we want to solve may not be linear. Also, in some puzzles, the values of the decision variables are restricted to be integers (that is, numbers with no decimal part): you can’t assign 0.8 of a crew member to a flight, for example.

Computers solve these problems by using algorithms: an algorithm tells the computer program exactly what to do and the computer chunks away and eventually tells you the best solution to the problem. The issue is how long it will take the computer to find the best solution, and in some cases the answer is disappointing: more time than the total time so far in the universe. Imagine a jigsaw so big that it would take almost forever to complete. In such cases, we may need to use a heuristic, which is a method that can get us an answer to such problems that may not be the best answer, but that we know it is a good answer.

In some puzzles, when you have found the best answer, you can easily confirm that the answer is the best. If, by luck, you pick up a jigsaw puzzle piece and it clicks into place, you know you are correct. With some mathematical puzzles, introducing randomness into the heuristic can speed up the process of finding a good, even best answer.

As the Nature article on the Abel prize says: “But since the advent of computers in the twentieth century, the emphasis in research has changed from ‘can an algorithm solve this problem?’ to ‘can an algorithm, at least in principle, solve this problem on an actual computer and in a reasonable time?’”

The winners of the Abel prize contributed to the solution of mathematical puzzles and to the field of computational complexity. Lovász has contributed to the solution of mathematical puzzles that can be expressed as movement on a network, seeking the best solution. Wigderson’s contributions relate to the use of randomness in finding solutions and relate to so-called zero-knowledge proofs, a way of proving that a puzzle has been solved without actually revealing the solution.

What does it mean for you?

Computers do more and more for us every day (just take a look at your cell phone), often relying on algorithms and heuristics to solve mathematical puzzles. We want them to solve bigger and bigger problems, so the answer is always, get a faster or bigger computer, but computational complexity helps the designers of algorithms know when a faster computer is likely to be successful and when the problems are simply too big to tackle. The results of computational complexity are important in guiding this work.

Paradoxically, sometimes we want to design problems that will take an enormous amount of time to solve; that idea forms the basis for most computer security. Guessing your 16-character password is beyond the reach of most computers. Complexity theory underlies cybersecurity and encryption, the methods that are meant to keep your information safe from attack. It also forms the computational basis of crypto currencies such as Bitcoin.

Where can you learn more?

The Britannica article on optimization is a nice introduction to the field, including some history. This article from Forbes discusses the types of business problems that can be solved by mathematical optimization. The professional organization INFORMS is one of several for professionals in optimization and computational complexity; they have an excellent history of mathematical optimization here.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Source: Wikimedia.This file is licensed under the Creative Commons Attribution-Share Alike 4.0 International license.

What’s new?

One of my former graduate students is now fairly high up at Facebook Reality Labs and she sent me an Oculus Quest 2 (also a charger and an Elite Strap). I have now subscribed to Supernatural and I am exercising more than I have in decades.

What does it mean?

The Oculus Quest 2 is a fairly bulky, but surprisingly light, set of goggles and two controllers, one held in each hand. Activation requires a Facebook account and use requires a wifi signal. Supernatural requires the associated phone app. Setup was trouble free for me. An Oculus Quest 2 costs $300 for 64GB storage and $400 for 256GB, including shipping in the US. A Supernatural subscription costs $179 for a year.

In Supernatural, I can select from exercise videos of High, Medium, and Low intensity (and from meditation videos) of various duration (from as short as 8 minutes to as long as 45 minutes). Inside my goggles, I am placed in a beautiful outdoor location (including one on Mars). I appear to be standing on a computer-generated mat, usually several feet off the ground. I can move to look around and up and down in the scene. A new video is issued each day and hundreds of old ones are available. I have created a list of my favorites.

The exercise routine starts with a warmup from a coach who is located on a computer-generated mat about 10 feet in front me and then consists of several songs (usually rock, pop, hip-hop, etc.). During the routines, my hand controllers appear to be light sabers (called bats in Supernatural) with which I strike at oncoming spheres, black for targets to be struck by the black bat in my left hand and white for the white bat in my right hand. My accuracy and power scores are recorded and reported to me between songs and at the end of the session, which ends with a cool down from the coach. During the entire session, the coach’s voice provides encouraging (and sometimes amusing) comments.  

The quality of the vision is remarkable. I have set my initial room in Oculus to a place in a Japanese inn, with a view of an outside street scene and nearby pond of fish. When I move around, the view changes with 3D fidelity. The sound is also very good. When I am standing in the exercise mat in Supernatural, several feet off the ground, I have to keep reminding myself I am standing solidly on my house floor. I have my goggles adjusted so I get a slight view of my real floor if I glance down past my nose, keeping me oriented.

For use while standing, as I do in Supernatural, the Oculus interface requires me to set a safety perimeter in which there are no objects, and it generates a visual signal if I move any part of my body outside that perimeter. Because its use is linked to a Facebook account, privacy issues arise. A friend created a second Facebook account just to use with Oculus.

I have gone through three waves of emotion concerning Supernatural. First, I immediately loved it: this is fun! The movements, the dance, and the exercise all felt great. Then, as I got used to it, I started to pay attention to the two scores: accuracy in hitting targets and power, scored relative to expectations based on my most recent performance. I started to try to get 100% accuracy and high power scores. I hurt my shoulders and the fun decreased. Now I am back to focusing on the fun and ignoring the scores. The strikes and movements are, I now realize, really well choreographed and I focus on feeling that movement. I am back to: this is fun!

In my seven decades of life, I have sometimes exercised a lot, sometimes less, and recently, (now dogless, so lacking any canine friend I always called my personal trainer), I have had trouble making a habit of exercise. I am, with Supernatural, exercising 30 to 40 minutes every day, with noticeable results. I have to pace myself so that I don’t overdo my workouts and hurt myself. Supernatural is fun! The Supernatural Facebook page has ample evidence that it has changed many lives for the better.

What does it mean for you?

Virtual Reality (VR) has been touted as useful for training and now I get it. The view from inside the goggles is not perfect, but it is remarkably good; most noticeably it tracks my movement adjusting the scene flawlessly. It is so good that when I tried a roller coaster ride app, I noped out of that very quickly. Also, the hand controllers allow for various interactions with the virtual reality, including grasping and using objects.  

The Virtual Reality Society provides a list of applications in various areas. In their business category, they list virtual tours of a business environment, training, and a 360 view of a product. VR gaming is very popular, including opportunities to interact with others.  “The best VR apps of 2021” at digitaltrends includes apps allowing the user to create spray graffiti, to watch 360 videos, and to explore 12 underwater environments, This example at Lenovo reports on the use of VR to restore memories for dementia patients

My three stages of emotion in Supernatural reinforce my belief that scoring systems designed supposedly to motive people actually undermine intrinsic motivation and thus long term behavioral change. As a professor, I told students that grades undermine learning.  Alfie Kohn has written great books on motivation, especially in the field of education.  I recently learned of a quote from Barry Schwartz (a professor of psychology at Swarthmore College, my alma mater): “when you rely on incentives, you undermine values.”

Where can you learn more?

The tag line on the TV improvisational comedy show “Whose Line is it Anyway” is “where everything is made up and the points don’t matter.” Or on video here. 

I read the Barry Schwartz quote in a recent report from the NAACP: “Fossil Fueled Foolery. An Illustrated Primer on the Fossil Fuel Industry’s Deceptive Tactics.” The second edition, issued on 1 April this year, is anything but an April Fool’s joke and I highly recommend it.

Alfie Kohn’s website describes his books; my favorites are Punished by Rewards and No Contest. In his latest blog post (8 March 2021) he quotes one of my heroes, John Dewey, on the bad effects of sugar-coating. Kohn remarks: “These days an awful lot of such sugarcoating is done digitally — for example, with apps that add points and levels to `gamify’ a list of decontexualized facts or skills that students are required to master.”

Virtual reality involves immersion in the computer generated environment. In augmented reality, additional information is displayed on top of person’s real view. The Oculus Quest 2 has a pass through feature for augmented reality, used, for example, to set up the safety space. Wired has a good introduction to VR with explanation of some terms also.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Source: Wikimedia Commons. This file is licensed under the Creative Commons Attribution 2.0 Generic license.

What’s new?

Since 23 March, a quarter-mile-long container ship, the Ever Given, has been stuck across the Suez Canal blocking all traffic in both directions.

What does it mean?

While news reports about this situation are mostly focusing on the efforts to move the ship and on the possible consequences for world shipping (do we need another reminder of the risks of long supply chains?), potential causes that have been mentioned include strong winds and a loss of steering power on the ship. Another report said that mechanical or engine failure had been ruled out and that the ship had been involved in an accident involving high winds in Germany in 2019.

What does it mean for you?

In Fall 2006, I was teaching, as I did each fall, an introduction to industrial engineering course at Colorado State University-Pueblo. My goal in that course was to help students get the big picture of industrial engineering, including that industrial engineers tend to blame the system, not the individual person, when mistakes and accidents occur. I told the class that initial reports of accidents often cite operator error as the cause, but that later reports often uncover deeper, systemic causes.

The next week, tragically, in Lexington KY,  a small jet took the wrong runway for takeoff, overran the too short runway and all but one of the 50 people aboard died; in an early news article, the cause was cited as operator error by the pilot for taking the wrong runway. As the class and I watched the evolving story over the semester, it emerged that the airport was undergoing construction and runway entrances had changed the week before; that, contrary to FAA guidance, only one controller was in the tower and he had turned to perform administrative tasks; that, again contrary to FAA guidance, the controller had been given multiple responsibilities; that small commuter planes were not required, as larger jets were, to have an onboard system that checks for the correct runway; and that other factors may have contributed to the crash. While it is clear that the pilot and copilot missed cues that they were on the wrong runway and engaged in irrelevant conversation while taxiing, the FAA took several actions as a result of the crash to improve the systems for ensuring use of the correct runway.

In writing this blog post, I found a 2019 analysis of the crash that stated that some of the lights on the correct runway were not working and that Comair practice did not include comparing the “heading bug” and the actual heading on the display.  That article stated: “Because it’s impossible to expect a pilot to never make a mistake, redundant systems exist to ensure that mistakes are caught and corrected quickly.” That article also states: “The nuance of the situation unfortunately was lost on many. The media largely blamed the pilots without recognizing that mistakes are never made in a vacuum.”

Tools exist to analyze systems for risks before accidents occur and to analyze causes after accidents. For example, my local Boys & Girls Clubs (I sit on their Board) recently instituted procedures for recording and analyzing mistakes that might have resulted in an issue concerning safety of club members, whether or not something bad happened. Kid safety is a strong priority of the Boys & Girls Clubs of America.

In my experience as an engineer, good engineers are obsessed with preventing mistakes and accidents, in a strangely matter-of-fact way. On a visit to a manufacturing plant years ago, my small group had gotten a thorough safety briefing and were outfitted in hard hats, safety glasses, steel toed shoes, orange vests, and more. As we left the briefing room to start the tour, we descended an external staircase. The engineer leading our group turned around to make sure that each of us was using the handrail on the stairs. I smiled.

“About 12% of world trade by volume“ goes through the Suez Canal. This episode has resulted in no loss of life or pollution, but the design of a system to keep the Canal open is vital not just to Egypt but to the world. An article by Captain George Livingstone calls attention to the systemic issues created by the ever increasing size of container ships.

Every accident or near miss should be analyzed and systemic improvements should be generated and considered to prevent future occurrences. Another industrial engineering principle is that workers work in the system; managers work on the system.

Where can you learn more?

Techniques for analyzing risk and discovering the root cause of errors include: FMEA,  mistake proofing, and the 5 Whys. The 2015 version of ISO 9000 certification focuses to a great extent on risk management.  

The fascinating book The Box by Marc Levinson describes the development of the shipping container and the changes that were required to the entire shipping system.

This work is licensed under a Creative Commons Attribution 4.0 International License.

What’s new?

A 16 March article in Automation World describes a new Stanley Black & Decker device (called the Inj3ctor) for manufacturing products from rubber by combining capabilities of injection molding and 3D printing.

What does it mean?

In the engineering program I used to chair, the course in manufacturing processes uses the well known textbook Introduction to Manufacturing Processes by Mikell P Groover, now in its 12^th edition. As shown in the table of contents, the book covers materials and then describes a great number of  processes such as casting; extrusion; coating; injection, blow, and rotational molding; pressing and sintering; forming; rolling; forging; drawing; machining; turning; drilling; grinding; annealing; plating; welding; assembly; fastening; and more.

Of course, any product is manufactured from a variety of materials using a variety of processes. Indeed, the crucial engineering knowledge is design, which involves selection of appropriate materials and processes to create a product with the capabilities desired by the customer. Look around you and just about any object you see was manufactured using a variety of processes in various combinations: a pen, a cellphone, a chair, a door.

The idea behind the Inj3ctor is not revolutionary – a mold is 3D printed and a flexible material, such as rubber, is then injected into the mold – but the marketing of the product as combining these manufacturing processes caught my eye.

What does it mean for you?

Right now, additive manufacturing is somewhere between experimental and routine, with new processes being invented and some processes becoming routine. The change in name from “rapid prototyping” to “additive manufacturing” indicated the trend toward making these processes routine. The make-versus-buy decision and distinction between the specialized shop and a general manufacturing plant will affect how much additive manufacturing get integrated into other processes or remains stand-alone, but the Inj3ctor tells me that additive manufacturing is well on its way to becoming routine.  

In your manufacturing processes you are probably very much aware of places where additive manufacturing is being used, just as you know where you are using casting, molding, forging, or drilling, but in the future you will think less about the new or different aspects of additive manufacturing and think more about its use simply as another manufacturing processes. Engineers will routinely consider the materials and processes of additive manufacturing as part of their design of products.

Where can you learn more?

The best places to follow developments in additive manufacturing are still magazines and companies particular to those processes, for example, the information from Additive Manufacturing Media or this outlook from the company FormLabs. Another window into additive manufacturing is through applications in specific industries, such as medical devices or sports equipment.

General manufacturing magazines also cover additive manufacturing: Manufacturing Engineering from SME (Society for Manufacturing Engineering), Industrial Machinery Digest, Manufacturing News, Manufacturing Today, The Manufacturer, and more.

This work is licensed under a Creative Commons Attribution 4.0 International License.

What’s new?

As part of its series on Most Innovative Companies, Fast Company published an article titled “The 10 most innovative manufacturing companies of 2021.” These ten companies were selected for their innovations in manufacturing processes. The icons on this link take you to other specialized lists in the Fast Company series.  

What does it mean?

Three of the companies contributed to the rapid response to COVID-19. SiO2 Material Sciences developed a better process to create a glass coating inside plastic vials. Carbon’s new product of improved nasal swabs was designed and launched in three weeks. Ford was cited for moving quickly to turn its designers and manufacturing facilities to producing PPE and ventilator products.

Four of the companies use 3D printing. Gantri was cited for using 3D printing to create custom designed lamps, Arris Composites for using additive manufacturing and molding to create better composites, Carbon for designing and 3D printing a better nasal swab, and Velo3D for innovations in metal additive manufacturing.

Sustainability is improved with several of these companies, often through its choice of materials. Gantri prints its lamps from plant polymers. Okeanos produces packaging with reduced environmental damage.

Lockdowel makes hardware for easy and fast assembly of wood products such as cabinets, closets, and furniture. The company is an example of a provider in a long chain, often invisible to the final consumer, that results, if done well, in superior products and lower costs: in one application, Lockdowel hardware is incorporated into cabinetry kits bought by home builders. The company has a wonderful set of videos on YouTube, showing their manufacturing processes and the use of their products. The company feeds my fascination with fasteners, an often neglected aspect of engineering design.

Instrumental provides in process inspection of products with computerized analysis of the images to detect product defects rapidly. SendCutSend provides fast laser cutting services for various materials, from steel, through carbon fiber, to wood.

What does it mean for you?

Among Fast Company’s many lists about innovative companies, I selected the list about manufacturing companies to emphasize that innovation matters in product design but also in the design of the process for making a product (or delivering a service). Industrial engineering, which is my area of expertise, is all about efficiency, quality, and safety in making products and delivering services.

These companies indicate several trends in industrial engineering, such as additive manufacturing, improved materials, and sophistical use of information technology. They also illustrate long-standing principles of industrial engineering, especially the emphasis on improving efficiency, quality, and safety.

Industrial engineering and sustainability are, I think, increasingly merging, to create a systems view supporting the three pillars of sustainability: people, planet, and profit. Your organization can’t afford to neglect any of these three. How do you find people who can take this broad systems view? Look for industrial engineers.

Where can you learn more?

The professional organization for industrial engineers is the Institute for Industrial and Systems Engineers IISE). Notice the crucial word “systems.”  IISE has links to videos, articles, webinars and podcasts about industrial engineering.

This work is licensed under a Creative Commons Attribution 4.0 International License.

What’s new?

A 1 March article at Brit describes 15 clothing brands that are moving to be more sustainable.  For example, the brand YES AND states its commitment to organic cotton, fair labor, low impact dyes, and lasting quality. Selva Negra “is rooted in the use of ethical practices and is committed to ethically sourced materials, production transparency, zero-waste packaging while picking up new ways to reduce their carbon footprint.” Made Trade sells items that adhere to “one or more of Made Trade’s seven core values: Fair Trade, Heritage, Made in USA, People of Color Owned, Sustainable, Vegan, and Women Owned.”

On 2 February, the government of the United Kingdom released a report commissioned by HM Treasury, The Economics of Biodiversity: The Dasgupta Review, named after Professor Sir Partha Dasgupta, the Cambridge University professor who led the work.

What does it mean?

In a previous blog post about fashion, I noted the limits of “Reduce, Reuse, Recycle,” I argued that consumers can’t improve the sustainability of fashion on their own, and I urged manufacturers to consider designing their production processes to support a circular economy.

As an engineer, I believe that technology bears some blame for the ills that beset our society, but I also believe that technology can do much to improve society. Electric vehicles, with batteries charged by renewable energy, may help sustain the personal mobility that many seek. Changing the fashion industry so its production processes are more sustainable is a feasible and worthwhile goal. The companies described in the Brit article are doing good work.

The pink sweater at the top of this post is my favorite piece of clothing. Purchased over three decades ago, it was, I remember, rather expensive, but it has been well worth whatever I paid for it. As implied by the brand name Au Coton, it is 100% cotton; also, it is made in Canada, virtually indestructible, and never out of style (well, I am not very style conscious, so it has also been, I am sure, never highly in style). I rarely feel a connection to Marie Kondo’s injunction that we should retain only those possessions that spark joy, but this sweater does do that for me.

But sometimes I also feel that I have failed in my role as a consumer by not buying new sweaters and thus fueling our economy. That’s a silly feeling perhaps, but so-called advanced societies measure their well-being by their growth. A static economy is bad and a shrinking one is a recession, very bad. Keeping a sweater for 30 years does not fuel economic growth.

The good news for those who want growth is that many other humans are more fashion conscious than I am. I was struck by the recent attention given in social media to a shoe, described in this tweet from Museum Archive as a “2300 years old Scythian woman’s boot preserved in the frozen ground of the Altai Mountains.” The decoration on the sole is designed to be visible when the wearer sat on her knees, socializing around the fire. The shoe is in the collection of the State Hermitage Museum in St. Petersburg. My conclusion is that fashion may have been invented before agriculture, before the wheel, even before homo sapiens.

What does it mean for you?

Despite my purchase of the pink sweater and other items from Au Coton, the company went into bankruptcy in 1993, but continued until 2003 in Canada, finally closing down “after the brand could no longer compete with conglomerate big box stores like Gap or Old Navy.” The brand is back now in Montreal and online; I am looking for another investment I can make in clothing that I plan to keep for another 30 years.

But the cautionary story of Au Coton raises the issue of whether a company can survive by selling clothing that lasts for 30 years. The Au Coton clothing is no longer made in Canada, but is stated to be sweatshop-free. Making items that last that long may be good for the earth, but not good for the economy, for jobs, and for growth.

The most widely cited definition of sustainability, from the Brundtland Commission in 1987, says “Sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” Note the pairing of “sustainable” with “development,” a phrasing used to balance the concerns of developed and developing countries.

The Dasgupta report offers another economic path. It urges us to recognize nature as an asset, “just as produced capital (roads, buildings and factories) and human capital (health, knowledge and skills) are assets. Like education and health, however, Nature is more than an economic good: many value its very existence and recognise its intrinsic worth too.” The report states next, “Collectively, however, we have failed to manage our global portfolio of assets sustainably.”  “Nature’s worth to society … is not reflected in market prices because much of it is open to all at no monetary charge.” Worse, many of our institutions not only fail to manage these externalities they actually pay “people more to exploit Nature than to protect it, and to prioritise unsustainable economic activities.” Our economies must be viewed as embedded in Nature. (The quotes are from the headline version of the report, available here.)

Its three recommendations are: (1) “Humanity must ensure its demands on nature do not exceed its sustainable supply….”  (2) “We should adopt different metrics for economic success.…” (3) “We must transform our institutions and systems – particularly finance and education – to enable these changes and sustain them for future generations.…”

With its first recommendation, the report notes: “But if we are to avoid exceeding the limits of what Nature can provide on a sustainable basis while meeting the needs of the human population, we cannot rely on technology alone: consumption and production patterns will need to be fundamentally restructured.”

Concerning the second recommendation, GDP is useful for some analysis, but its failure to account for the depreciation of natural assets, encourages us to pursue unsustainable development. National accounting systems must include natural capital.

Finally, money has to flow to support the maintenance of crucial natural resources. For examples, nations could be paid by other nations to protect the ecosystems on which we all depend. Also, education must reconnect people with nature so they demand these changes.

We need to have an economy in which producing and buying a sweater that lasts for 30 years or longer is common.

Where can you learn more?

A short description of The Dasgupta Review is here. The full report and other shorter versions are here. The Royal Society has a video discussion of the report here.

Various commentaries on the report express hope that it will have a large impact in improving our future: The Nature Conservancy, GreenBiz, the UN Environment Programme World Conservation Monitoring Centre.

What’s new?

On 18 February, NIST (the US National Institute for Standards and Technology) announced Release 4.0 of the NIST Framework and Roadmap for Smart Grid Interoperability.

What does it mean?

History shows us that the world has become more interconnected. The future of technology lies in even more networks and systems. Exhibit A is the Internet, which has revolutionized information flow and communication, but, looking further back in history, electrification, the interstate highway system, the telephone system, the railroads, and many more examples demonstrate the powerful effects of interconnection. But each of those networks is littered with the detritus of failed interconnections due to lack of compatible standards: train track width, DC or AC electricity, and so forth.

Beneficial electrification has great potential for reducing climate effects of electricity generation if the electricity can be generated from renewable energy. While the sun doesn’t always shine and the wind doesn’t always blow in one location, renewable energy (including hydropower and geothermal sources) is reliably available somewhere not far from where you need that electricity. Thus, interconnection, along with the many types of storage of energy being developed, hold promise for reliable electricity generation that may help us save the planet. But such interconnection relies on compatible standards for electricity flow, for communication about needs and availability of electricity, and for control of the devices that consume and produce electricity.

Interoperability focuses on the communication part of those interconnections. From page i of the NIST report, “Interoperability — the ability to exchange information in a timely, actionable manner — is a critical yet underdeveloped capability of the power system. Significant grid modernization has occurred in recent years, but the proliferation of technology and associated standards has only modestly improved interoperability.”

Also, from the same page, “The benefits of interoperability are broad and reach all stakeholders at all scales. … by allowing coordinated small actions across diverse stakeholders and devices to have grand impacts.”

We’ve been through this before, many, many times. We know how to have the many stakeholders work together to set standards and create regulations that ensure interoperability, while still allowing, in fact encouraging innovation to flourish.  We also know how to break the standards apart so that an engineer designing, say, an inverter, can refer to standards that cover the interoperability issues for inverters and not need worry about interoperability issues that affect only high voltage transmission lines or electric vehicles.

The increasing variety of generation sources and locations means that the grid needs to have more communication among these devices. Also, consumer devices (refrigerators, air conditioners, washing machines, etc.) increasingly come with sensing and communication capabilities that allow the owner – or the utility – to control when and how that device operates. While the electric utility industry refers to these devices as being “behind the meter,” that is, on the user’s side of the electric meter, they really are part of the grid because their communication capabilities offer huge potential to dynamically balance the supply and demand for electricity. Again, the grid needs more communication interoperability.

What does it mean for you?

Interoperability is an issue for all information technology. You can use any mouse with any computer (well, not quite, make sure the plug is compatible, and you may need an adapter) because there are standards for how the devices communicate. You, as the consumer, just shouldn’t have to worry about interoperability.

Your relationship as a consumer, as a manufacturer, or as an operator of any organization, with your electric provider is changing. If, for example, you have solar panels on your home, you may buy electric power but also sell it to your utility. If your organization has equipment that uses large amounts of power, you should already be working closely with your electric provider and you will be working even more closely with them in the future. For example, you might implement a soft start for your machines after down time in order to avoid adverse impacts on the grid. These interrelationships will increase with increasing abilities of new devices to sense, communicate, and be controlled.

Just as we have become providers of information used by others through our activities on social media, our devices will be wired to provide information, raising the same issues as those raised by our use of social media, most notably, who owns, benefits, and controls the information generated by the devices in our homes and factories. The NIST report states (page 6) “An empowered energy consumer has many opportunities to obtain value and can optimize their interactions with the broader energy system to maximize their preferred benefit,” but I fear that the consumer may not be the one defining this new relationship. The NIST report notes on page 58, “Absent an environment that allows universal access to the full range of opportunities, customers may be required to select devices and systems for feasibility of integration rather than the operational or economic value propositions they offer.”

Interoperability is necessary for this improved communication in all parts of the electrical grid, but it comes with its evil twin, a possible lack of security. Thus, this report also covers the need for security aspects in this new interoperability.

Where can you learn more?

The NIST statement concerning the new report has helpful information on interoperability. The report itself has a summary called Key Messages, which I have quoted from. The US Office of Electricity (part of the US Department of Energy) has a helpful page on grid modernization.

The Electronic Frontier Foundation (EFF, “The leading nonprofit defending digital privacy, free speech, and innovation for 30 years and counting!”) has noted the privacy threats of the smart grid, but with a focus on households. I cannot find that any business or manufacturing group (for example, the National Association of Manufacturers) is watching the developments in interoperability of the electrical grid.

An article on the McKinsey website argues that utility companies have not described clear benefits for consumers from grid modernization.

What’s new?

In May 2020, Lori Beckman wrote at Production Machining about the company MachineMetrics. She quotes Eric Fogg, co-founder and COO of the company: “MachineMetrics can collect any data that is useful to a customer,” he says. “That data can be whether the machine is running, how many parts it has made, and its alarm history, for example. We take all the data, encrypt it and forward it to our cloud service where we perform analytics and create dashboards for our customers to use.”

What does it mean?

Most machines on manufacturing floors are ready to be part of the IoT, Internet of Things, that is, a network of devices that share information; they include sensors and data collection. MachineMetrics can easily connect its device (MachineMetrics Edge) to almost any machine (through the machine’s ethernet port). The device reads the data from the machine and sends it wirelessly to software that will store, analyze, and display the data, combined with data from other machines. Data as simple as status of the machine can be used for asset management, machine utilization monitoring, and real time alerts when repairs or adjustments are needed.

What does it mean for you?

Collecting and analyzing data is done for two major reasons. The first is to make better decisions. One of my areas of expertise, decision analysis, stresses this purpose for data. Decision analysis even has methods for determining the expected value of information, and for determining if collecting data is likely to be worth the cost of doing so.

The second major reason for collecting data, somewhat in contradiction with the points I just made, is to achieve understanding, often for long run purposes and not for any immediate improvement in decision making. One of my first professional jobs, while I was in graduate school, was for the corporate planner for a large medical group. One of his overall goals was to use data to reach a solid understanding of the organization as a system and of the organization as part of the larger medical system. For example, in one study I analyzed employment records to seek to understand the plausibility of some commonly held beliefs about physicians using the organization to establish themselves in a new geographical region before setting up their own practice. We found only weak evidence to support the belief, not enough to worry about the impact of this behavior on the organization. This study was just one small piece adding to the understanding of the system.

Collecting data to make better decisions gives a focus and structure to thinking about data. What decisions do you or others in your organization make? They range of course from strategic (should we acquire that company?) through major (should we purchase a new piece of equipment?) to daily (which job should be done next on which machine?). Decision analysis focuses your thinking by requiring you to explicitly state the alternatives, the uncertainties concerning what occurrences will follow, and then ensuing decisions and occurrences. A decision tree (see the small one at the top of this article) is a visual representation of that sequence of decisions and occurrences. With such a visual representation, you can then ask what type of data would reduce uncertainty about future events and enable better decisions to be made now.

Collecting data to achieve understanding can also be valuable, but it is sometimes a way to bury oneself in data and confusion. In my job with a medical group, I learned a lot about data analysis, but I also learned a lot about system modeling. The tools for data analysis 50 years ago did not allow the powerful search for patterns in large databases, so we rarely (probably never) simply looked for patterns, nor did we often collect new data. Instead I learned a lot about how to formulate a good question about how a system works and then to use existing data bases to explore answers to that question.

Data collection tools like those offered by MachineMetrics can help your decision making and can help your understanding of your organization as a system, but data can also bury and confuse you. For example, what is measured and monitored may become a goal that distracts from what cannot be measured or monitored. If you are measuring and focusing on productivity but not on job satisfaction, you may have good short term and poor long term results. Monitoring of machine utilization might lead to an incorrect focus on increasing machine utilization to the detriment of other organizational goals.

The first example in the MachineMetrics article at Production Machining can, in fact, be read as a cautionary tale in which the newly collected data made the shop’s managers finally listen to the machine operators’ insistence that machine break downs were slowing productivity. Isn’t this story really about communication between people, not between machines?

Always ask yourself about any data collection: will it help me make better decisions? If not, will it help me understand my organization as a system? Don’t just collect data because you can. Don’t be misled into thinking that gathering more data is always good.

Where can you learn more?

An Internet search on “decision tree” or “decision tree analysis” will lead you to many useful pages with an introduction to this technique, such as here (a 1964 Harvard Business Review classic), here, and here. Decision tree analysis relies on the question “What happens next?” Many business degree programs and probably all MBA programs include decision analysis. I still think the best introductory book is the 1968 Decision Analysis: Introductory Lectures on Choices under Uncertainty, by Howard Raiffa. When I wrote this blog posting, Better World Books had used copies for $5. Software exists to help you create and analyze decision trees. My favorite is TreeAge.

The IoT, Internet of Things, doesn’t necessarily mean connecting everything to the Internet. The “Things” in the Internet of Things are devices that have built-in sensors, communication capabilities, and controls. These are connected with each other to collect data and to enable control of this network of devices.  A simple example is when your mobile phone connects to your car so you can take a call hands free. The IoT relies heavily on shared protocols for data format, so interconnectivity is a crucial capability of any device your organization acquires; interconnectivity’s evil twin is computer security, also a crucial capability.

What’s new?

This week I read three articles on materials and thought about justice.

The website Interesting Engineering reported on a new method to make transparent wood. The previous method, which removes the lignin from the wood, requires excessive time and high temperatures, produces excessive liquid waste, and weakens the wood. The new method uses hydrogen peroxide and light to change, rather than remove the lignin molecules. Transparent wood has potential application in stronger windows and roofs with better insulation properties.

NIST (the US National Institute of Standards and Technology) reported on a new method using nanoparticles of silicon dioxide (quartz) to create a gel of oil and water, two liquids notorious for being difficult to mix. The resulting gel has many potential applications, for example in filtration, in smart windows, in battery technology, and as scaffolds for cell growth. The new method can potentially be used with other nanoparticles to create other useful gels.

The 30 January 2021 issue of the science news magazine New Scientist contains a review by Simon Ings of a new book The Rare Metals War, by French journalist Guillaume Pitron, about the environmental, social, and political consequences of human success in creating and using materials. The review contains these intriguing sentences: “Before the Renaissance, humans had found uses for seven metals. During the industrial revolution, this increased to a mere dozen. Today, we have found uses for all 90-odd of them.”

What does it mean?

Transparent wood? Mixing oil and water? Those two stories sound, at first, like science fiction or a joke. What is next, liquid dirt? Or solid air? The existence of new processes for making transparent wood and for mixing oil and water amazed me, but I was amazed even more to learn that other processes to create those products already existed. The inventions described in the first two articles are new processes, not new materials.

Two points are relevant to almost any discuss of materials. First is that the history and future of science, technology, and engineering involves new uses of old materials and the creation of new materials from the limited number of elements that exist in nature. Second is that the creation of new materials requires also the invention and improvement of methods to manufacture the new materials. Note that those two points meet where scientists manufacture new elements, extending the periodic table.

I am excited by these developments about new materials and their importance in so many fields, including battery technology, renewable energy, medicine, building construction, and communication and computing technology. With the removal of hemp (cannabis with less than 0.3% THC) as a Schedule 1 controlled substance in the US farm bill at the end of 2018, I think that new uses of hemp will explode. Scientists and engineers are creating amazing new materials and amazing new process for making those materials.

Returning to Pitron’s emphasis on metals, rare or otherwise, prehistoric human use of gold, copper, silver, lead, tin, and iron was accelerated by an explosion of discoveries of other metals and a parallel explosion of inventions that often relied on creating new combinations and thus new materials.  The development of the first metallic alloy, bronze, from copper and tin, is so important it has an age of human development named for it. The Bronze Age was named for an alloy and was succeeded in human history by the Iron Age, named for an element, but really only taking off when humans developed alloys of iron, notably steel, an alloy of iron and carbon. The timeline in this history of metals is fascinating.

The word for each of those metals (gold, copper, silver, lead, tin, and iron) can be and is almost naturally followed by the word “mining,” and human history can be described, with perhaps only some exaggeration, as digging stuff out of the ground, creating an object that to use for a while, and then throwing it back into the ground. Our knowledge of early humans to a large part relies on the fact that we seem to be continually shedding objects.

The review of Pitron’s book makes clear the costs to humans and the environment of this obsession with making new stuff and also makes clear that the geographical dispersion of those effects has political impacts. But even more, the review summarizes Pitron’s argument that our worthwhile efforts to be more responsible through the new of renewable energy may exacerbate these impacts. Many of the new technologies, especially for batteries, rely on the mining and refining of the so called rare earths (actually metals) and other elements such as tellurium, cobalt, and lithium. Those processes have been dominated by China, fueling both its economic success and its horrible air pollution. In his review, Ings writes that these effects on China “wouldn’t have been possible had the Western world not outsourced its own industrial activities, creating a planet divided, as Pitron memorably describes it, `between the dirty and those who pretend to be clean.’”

Ouch.

The historic steel mill in my hometown of Pueblo already uses only recycled steel and, with a solar field under construction, will be powered only by renewable energy by the end of this year. Our newly elected Congressperson recently objected to the US rejoining the Paris Accord with the tweet “I work for the people of Pueblo, not the people of Paris,” a laughably ignorant remark which resulted in predictable push back from a city that can be plausibly described as a renewable energy hub  and “as a place that is leading the way in the transition to a clean energy economy.” We already host a factory manufacturing towers for wind turbines.

But Pueblo also hosts the Comanche power plant which burns coal to power Denver, 100 miles to the north. The electricity powering the computer on which I am writing this blog comes from my rural electric cooperative, but almost all of that energy comes from a cooperative of cooperatives, Tri-State, which is frantically trying to meet demands to move from coal to renewable energy. The State of Colorado is also struggling with how to help coal-dependent communities make a just transition.  About 70 miles to the south of Pueblo is the site of the Ludlow Massacre, commemorating the deaths of 25 people in 1914 in the Great Coalfield War, described by George McGovern in his 1972 book with that title.

What does it mean for you?

At this point I want to energetically wave the word “system” and throw up my hands in frustration. Even if all actors are genuinely honest and caring and want to save our planet, the path for these necessary transitions is sometimes hard to discern because of effects both near and distant – in time and geography – of any action we take. I am, however, increasingly convinced that “justice” is a key word in that path. To state the obvious: different paths forward affect different people around the globe in different ways.

I joke that unless we do better, the pitchforks and torches will come out. I urge you to study the picture at the top of this article.

Where can you learn more?

An Internet search on the phrase “climate justice” will lead you to excellent material supplied by websites such as the NAACP (if you click on only one link from this blog, choose this one), the UN Sustainable Development Goals, the Climate Justice Alliance, the Indigenous Environmental Network, and many more. I am resisting my urge to quote at length from all of them.

What’s new?

The 2 Feb issue of the newsletter The Hustle contained a link to the 26 January report “Big Ideas 2021” from ARK Investment Management LLC. You can register with ARK to get a copy here or download from The Hustle here. The Hustle newsletter describes the top idea of the 15 ideas in that report: deep learning.

What does it mean?

Besides deep learning, the other 14 ideas are: the re-invention of the data center, virtual worlds, digital wallets, Bitcoin’s fundamentals, Bitcoin, electric vehicles, automation, autonomous ride-hailing, delivery drones, orbital aerospace, 3D printing, long read sequencing, multi-cancer screening, and cell and gene therapy.

For each Big Idea, the report explains what it is, assesses the potential for investors, and discusses related trends and effects. For example, deep learning, a type of artificial intelligence (AI), “uses data to write software,” and is aiding in the creation of conversational computers, self-driving cars, and consumer apps. It requires “boundless computational power,” “is creating a boom in AI chips,” and is “expanding from vision to language.”

The report goes into depth on the development of new computer chips to challenge Intel’s dominance, the effects of virtual reality and augmented reality on gaming, trends in financial services (digital wallets such as Venmo, and digital currencies such as Bitcoin), two technologies I have written about frequently (electric vehicles and 3D printing), the movement from automation from its success in manufacturing to other parts of the US economy, trends related to moving people and consumer goods (autonomous ride-sharing and delivery drones), and the growth in satellites to provide ubiquitous Internet connectivity.

The last three trends focus on biology and medicine. I learned that I need to read more about those areas. I need to learn more about what improvements will be enabled by long-read sequencing of genomes and about the technology of gene editing.

Their summary of EV trends (battery prices, range, performance, and sales) is succinct and persuasive that a roughly 20-fold growth can happen in the next five years. They connect 3D printing with improved drone technology and with the use of AI to optimize design.

I am surprised by some of their conclusions. The report has two trends related to Bitcoin, but a friend who invested early in Bitcoin tells me investors have moved onto other digital currencies. I find the potential applications of virtual reality in training to be more interesting than the report’s emphasis on gaming. I remain skeptical about autonomous vehicles without changes in the transportation system. Multi-cancer screening of asymptomatic populations faces, I think, the reality of signaling many false negatives (as driven by Bayes’s theorem). However, ARK is focused on where the money is and certainly has more knowledge than I do concerning that focus.

The report has no mention of climate change.

What does it mean for you?

What is ARK? Page 2 of the report states that ARK is an investment firm that “specializes in thematic investing in disruptive innovation and strives to invest at the pace of innovation.” What is a Big Idea for ARK? Page 4 states: “ARK requires a big idea to be investable and long-term.” My goal is not to give investment advice, but rather to help you be aware of and benefit from technological developments that may affect your organization in the future. The report focuses on how an investor can make money from these trends, but the report is still very helpful in pointing out trends for you to watch.

I have an engineer’s instinctual attraction to things that actually make better the lives of people and thus I find the report’s emphasis on making rich people richer (such as applauding the decline of labor’s share in the rewards of productivity) and its emphasis on the benefits of monetization of human activities not to my taste, but I recommend you read this report for some well written and researched information on trends. Perhaps you should view my engineering sensibility as merely resentment that the financial folks get much richer than engineers do from their own work.

Where can you learn more?

You can subscribe to The Hustle daily newsletter here. I find its over-the-top, well, hustle, wearying, but it is an interesting read for trends.

Regarding the 15 trends, I plan to spend some time doing Internet searches to learn more.

My money is invested through a fee-only financial advisor.