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Thanks for sharing – Vic

Anyways, thanks for sharing! – Aly

The decay has already begun with the outsourcing of many jobs, just to make the corporations more money. When less people have jobs, less things get purchased.

Outsourcing is SO obviously the cause of the current economic downturn. I am simply amazed that we are refusing to acknowledge the "Elephant in the Room" !!!

Worker "A"’s job gets outsourced. He cannot buy goods. He cannot make his House Payment.

Bank forecloses on House.

Multiply this by thousands, then millions.

Banks in danger of going belly-up. They get bailed out by Government DESPITE MANY calls to congressmen to NOT bail them out.

Banks give million-dollar bonuses to the very people that gave mortgages to the workers whose jobs got outsourced. And on it goes.

The house of cards is crumbling, because big business is always chasing SHORT-TERM profit and ignoring LONG-TERM consequences.

I believe one of the major stumbling blocks to the widespread use of Electric Vehicles is the same one that caused the Gasoline – Powered automobile to experience a slow rate of acceptance at first – the lack of a supporting infrastructure.

It was not until a sufficient number of Gas Stations was built nationwide, that the use of the automobile became practical.

Recharging Stations at the workplace and other stopping points, such as Malls, are needed.

But at the very least, it helps as the public is not sufficiently informed regarding the possibilities and practacalities of battery powered transport. The timing couldn’t be better in view of the well known underwater catastrophe swimming everyday towards the gulf shore.

I have a better idea of the mission of NCMS also.

The only thing I would have liked to have seen from the author is at least a nod to the challenge of what to do with all those batteries once they eventually "die"- – I have read elsewhere that the environmental impact of obsolete batteries could be staggering.

An engaging article… thanks!

Marie Elwood (http://www.avalaunche.com; http://www.speeddialnewsletter.com)

Regards

Tom

We just posted a podcast with Richard McCormack at the above link.

Regards

Bunzy

Regards

Gonzalez

Regards

Nimi

Regards

Loop

Regards and respect
Worker

Regards

Viki

One crucial matter is losing old skills, while not gaining enough new ones. The few manufacturers that I know that are seeking people can’t fill the skills at a pay rate they consider acceptable, and there’s a lot of old mythology about this. It’s not true that "anybody" can assemble a car with today’s technology to today’s quality requirements. But the "public" thinks they can, so they "look down" on the job. This do-it-cheaper mentality has us in trouble. And the UAW’s $70 per hour pay rate was largely bloated by health care and retirement loads that companies could no longer shoulder no matter how well anybody performed. We need to drop a lot of illusions about what really needs doing.

Software? Lots of good stuff. Some of it actually does what the programmers say it will do, and it’s so pervasive that a giant internet crash would bring the economy to its knees. Or what would happen if electrical power was shut down about half the time — as in places like Iraq? Do we have a highly vulnerable system that has evolved past the point of being able to regress to an earlier state and go a different direction? (Called a progress trap.)

New manufacturing jobs for millions of unskilled people is unlikely; that transition happened long ago, and it’s over. Manufacturing is the victim of its own success. For decades, there has been much more work to do moving stuff around or transacting it than in making it. By early 2009, almost 8 million people worked in occupations classified as financial services as worked in manufacturing (12.8 million in February) — and financial services presumably contributed 7.8% of GNP; manufacturing only 6.9%. But manufacturing is where the big labor productivity improvement have come. Now we have a consumption economy. As many people work in food service as in manufacturing; many services that we used to do at home we now pay people to do for us away from home (like prepare meals). Have no idea how many work flea markets trading "stuff" somebody no longer wants, but it’s not insignificant. And could Wal-Mart be classifed as just a high-grade flea market for stuff reprocessed through China? Somebody, someplace makes all this stuff, but it doesn’t take very many of them even in China. As a whole what does this economy look like, and why does it seem like a house of cards?

Statistics are flakey. Of the total number of people that are classified as working in companies with an industrial SIC code, how many actually make anything? (Peak "official" manufacturing employment in the U.S. was in 1979 — about 23 million by BLS stats.) Not only do companies compete with the "China price," in factory after factory, we import a lot of the workforce. English as a second language remains very common. And by the way, discounting the temp workers (many undocumented), less than a million people now actually work on farms (much less than live on farms). But what’s a farm any more? Food remains pretty important; agricultural labor productivity has risen about 20X in 50 years, and agriculture is been amply subsidized, but still more farmers keep dropping out. So what is it about our concept of success that really isn’t so successful?

Creating jobs has political appeal. Every pol in every country wants to blow about new jobs, but manufacturing jobs have declined in other old economies as much as in the United States, and in many cases more. (Japan has lost 25-30% in 20 years or so; France is down about 40%). Officially, manufacturing employment even in China has not risen very much, but numbers there are even flakier than here. See BLS 2004 report on this at:

http://www.bls.gov/opub/mlr/2005/07/art2full.pdf

China’s manufacturing employment (85-90 million) exceeds that of all OECD countries combined.

Biotech is the great new hope. Biotech and health care are the major growth areas in American manufacturing. Look at the new factories — lots of medical instruments and pharmaceuticals. Both government policy and customer demand has favored this — so far. Health care is one of the few areas where, despite attempts to hold down costs, expenditures keep going up. Give doctors new toys and they will use them, and their patients expect them to use them. A physician’s order is the trigger point for much of this expenditure, which is why many companies want to influence them, and they do as much as they can. Moral of the story: High tech and reduced costs do not necessarily go hand in hand. Need to re-think another old myth.

Otherwise, we have a mentality of "my brother in law can get it for you cheaper," and lots of executives must have married Chinese. But now even Mongolian garment workers are bitching about losing their jobs to the Vietnamese, and a standing joke is to put garment factories on barges and tow them to the cheapest port.

The federal government may not have a manufacturing policy (outright subsidization), but states and localities do. They compete with goodies and tax abatement to keep companies and jobs. That has been a big shift in the past 50 years or so. And still the factories blow away. We’ve been trying to prop up an increasingly wobbly system. [Maybe we got ourselves in an economic progress trap and have to fumble our way out of this rat maze.]

So what do we really have to do to turn all these negatives into a positive? It’s not like we don’t have plenty of talented people seeking challenges, and plenty of things to challenge them. We don’t have our heads screwed onto the nature of 21st century challenges yet. Can’t wrap our heads around what we really need to do and why.

http://www.americanmanufacturing.org/manufacturing-a-better-future-for-america/

Is it any wonder that this foolishness caused us to crash last year? These banks, so called, were and still are populated by financial manipulators, rather than real bankers. Electronic trading
at the speed of light has enabled these folks to operate globally and get rich at the speed of light. Maybe I’m old fashioned, but we have outfoxed ourselves. We need to go back to our roots, namely, make stuff.

If we can not, or will not, make stuff that other countries want to buy, we will no longer be a world military and economic power. Military power comes from economic power. Economic power means having a genuine manufacturing base, not just a services base. The latter can not support the high employment, high standard of living "middle class" which we have had and has been the envy of the world for so long. We are approaching 10% unemployment. Services will never be the solution for that ailment. Not everyone, for a variety of reasons, are well suited to writing code, selling advice or whatever.

Our government continues to borrow money from foreign sources, or just as bad, print it. As the value of our dollar declines, which is inevitable on our present course, our foreign lenders will demand higher and higher returns, or refuse to lend, ultimately leading to our loss of the advantage of having the world’s "reserve currency." Imagine the cost of commodities like oil when we can no longer pay for them with dollars? And having a political class that will not allow us to tap into known and recoverable "lower 48" reserves. It is all well and good to develop solar, wind and other energy sources, but what do we do in the meanwhile? It was Jimmy Carter, I believe, who created the Dept. of Energy, or some such, to decrease our dependence on foreign sources of energy. We are still waiting!

There is nothing but debt, and more debt, on the horizon. We need to start manufacturing again soon, or it will be too late. This is a horrible legacy to leave to our children and their children.

The one thing they didn’t do was draw the conclusion that I came to in my 2004 presentation for NCMS: that labor rates are crucial to manufacturing competitiveness and that currency exchange rates are a major determinant of labor rates.

Whether I’m right about that or not, we are now certainly reaping the whirlwind of 40 years of neglect and trivialization of manufacturing. I wish I could see an easy path back, but I do not.

It is not clear what the panel means by ‘manufacturing.’ Do they mean a) the process of turning information into products, or b) an industry, or c) an enterprise that interacts with other enterprises, or d) an economic sector or e) a way of provding employment, or f) an instrument for ‘social justice,’ or g) what? I encourage clarification of Context, then the Content and Structure that are Fit for (whatever) Purpose. With this clarity they might garner lots more support rather than just empathy.

The panel seemed more focused on problems than on opportunities. We can build systems for one of two reasons. One is to suppress problems, helping avoid the unwanted. The second is to create something we care about. Which is the NMCS focus? It is difficult to build a system that does both. It can be useful to focus on the impediments to achieving an objective provided that opportunities for overcoming the impediments are also identified. In fact, this is the core of strategy formulation. Then resource allocation and scheduling can be done for real.

Regarding action, Go Public. Preaching to the choir or to politicians (many of whom abhor the notion of corporation) is futile. Show the public why THEY are losing if ‘manufacturing’ loses.

Sort out an Order of Battle. Manufacturing cannot heal all leaks and sores simultaneously. Triage manufacturing and identify the 1/3 that can be made to dominate the global market. Trying to sustain Kueffel and Esser after the advent of the TI calculator was a waste of time.

Manufacturing materializes models. Without excellent models manufacturing is at a disadvantage. Engineering produces the models. The models may ordain a consumable product, e.g., a can of peas, an automobile, etc. or a transitive product, e.g. a CAD system or an autonomous manufacturing machine. Both CAD makers and U.S. schools are stuck on the product paradigm, not focused on model generators. Accordingly, NMCS should campaign for modernizing engineering.

The NCMS could understand economics as "exchange of value" then sort out the various kinds of value it could exchange and how to monetize the various kinds.

Regardless of the specifics above, an agenda for the better way for ‘manufacturing’ can be created by engaging a few knowledgeable, open minded people in an Interactive Management process aided by skillful facilitation and the Interpretive Structural Modeling software. See http://www.jnwarfield.com.

OBTW, throughout the video the Panel did not acknowledge any question or comment as adding value — only seized on each one to make a plaintive speech. As Einstein cautioned, they are going to have to come at this with a higher level of consciousness than they had when the caused it.

Onward,

Jack

some my personal ideas:
Education, I believe it is the key for manufacturing industry and the country to survive.

I like to combine country’s future with manufacturing, as I see all the past civilizations are evaluated first by their technology level to produce goods, which is essentially manufacturing industry. So I believe the future still depends on it.

Why Education?
> Because we are losing the young generations to maintain the industry.

Why “we”?
> Because China is facing similar problem, it just starts later than yours.

What’s the problem with young generation?
> Mao ZeTung once said: “Enemy (evil ideology) will pin the hope on the 2nd and 3rd generations.”
> My peers surrounding me, both Chinese and those from US: “What is manufacturing? Why choose that? Come to code web-games, sell houses, or be a trader at investment company. That’s how to become rich…” and that’s why the investors still only know about websites and real-estate.
> Professors of Manufacturing-related majors in Universities: “Sorry, I don’t have enough funding to support new Graduates…” I know many professors within the circle, they even have to compete with low level suppliers on projects without any innovation, just for the labs to survive. No young people will choose a manufacturing related career when facing an education like that.
> Check the European style: most company and industry build their own schools and breed their own successors. That’s how BOSCH can invest hundreds of million Euros for a single factory while the US auto-suppliers are in a mess with the Big-Three.

How bad is the manufacturing industry doing on education their successors?
> Very. My roommate saw the documentary movie of BMW product line THRICE just to say he want a BMW with a blond. And I know a US college student major in material forming who know nothing about mould but want a job in investment bank.
> Take Information Technology as example, it is important for upgrading manufacturing in the new century. However, for most high school students, IT = Department of Computer Science = a “dot-com” career or a job at the IT department in banks. They have on idea how all the other important disciplines such as manufacturing are evolving with information technology. And that’s why lots of CS graduates are not appreciated by industry executives. [M. Tomizuka, U.C. Berkeley, 2002]

two suggestions:
> pay more attention on young students. When they ask what is manufacturing, don’t shuffle about it can also earn a proper salary, just tell them: “all the things you wakeup to see in the morning are the products of manufacturing!”
> cooperate more with colleges – they need the industry’s money to breed the industry’s successors.

That said, I wonder if we are suggesting a tool before fully defining the problem. For example, in a prior life I worked an engineering information center. Found that half the job was probing what requesters were really trying to do before helping them use that old rickety system. That is, for the time, system capability was no problem; deciding what to do with it was. Doubt if the human element has changed much, so if reducing development time and loop backs is the objective, there’s more to it than simulation capability.

Of course, simulation requires validating that both model and data are relevant to design intent, but what of possibilities and data that are not known; not included in the simulation? I’m somewhat aware of Mike Gnam and Paul Chalmer’s work. They begin to address this. DfX is a huge shift toward integrative design. Unknowns and data gaps are common. If Decision Incite addresses this, I did not pick it up from their site. Many designers have a limited concept of DfX; and relevant data for it are not easy to come by if they do. That is, if designers are not clamoring for detailed simulation capability today, why?

Robert W. "Doc" Hall
Editor-in-Chief, Target
Association for Manufacturing Excellence

- COMMODITY COMPUTING meaning that the cost per CPU-Hr is now measured in cents, from 10 cents to 60 cents per CPU-Hr. There is no need to purchase expensive hardware as it is being offered on-demand from companies ranging from Amazon to IBM.

- MINIMAL ASSUMPTIONS as the Monte Carlo process used in Simuation Supported Decision Making is independent of the number of variables in the problem and is mathmatically simple. A friend who is an MIT mathmatician relayed that "the Monte Carlo process is NOT mathmatically elegent (meaning complex), but it just gives you the right answers." This changes the problem definition from historically making simplifying assumptions to solve the problem, to incorporating as many variables as possible (minimizing assumptions) and letting the computer analysis sort out what is important (vice assuming).

The key point is that engineering analysis has historically been deterministic, in which each variable has one value. We are now promoting stochastic simulation, in which each variable has a range of values (as in what really exists). Stochastic (or Monte Carlo) simulation enables significantly more information from a model, such as identification of relationships between variables, and outliers (combinations of variables that generate non-intuitive results.

The barrier to using stochasic simulation in the past has been the computational cost and time needed to run hundreds or thousands of analysis runs. Advances in computers have enabled stochastic simulation with CPU costs of pennies per hour. With this capability every engineering analysis should be done stochastically. I presently demo a simple stress calculation on an I beam in Excel on my laptop to show how much more information can be gained from a model using stochastic simulation. Car companies have been conducting stochastic simulation of car crash for years. The process is independent of problem size. Every analysis should be run stochastically to take variability into account and get orders of magnitude more information – because you can today for minimal extra cost with commodity computing.

Another key point raised by Jerome Aiello is with the need for this to be used by people who have real world experience ad understanding in what they are doing. A poor model will give poor results. (A side benefit that we have found with stochastic simulation is that it can often detect poor analysis models as the simulation will not run on some combinations of variables as a result of poor modeling practices.)

Simulation Supported Decision Making is a way to take advantage of commodity computing to provide a way to learn from "virtual" experience complementing out real experience.

Feel free to call or e-mail if anyone has further questions or would like more informaiton on SSDM. I can be contacted at geneallen@decisionincite.com or at 703-582-5554.

I SHOULD have said: "What you need is Shop Rats with an Associates Degree IN SIMULATION ENGINEERING"

I do not want to disparage Computer Science Majors, because they are talented and learned individuals. But what I typically saw, is that those were the types of graduates they were hiring to learn Simulation Engineering, and that was TOTALLY wrong !

What Simulation Engineers need the MOST is HANDS-ON knowledge of THE PROCESSES THEY ARE TRYING TO SIMULATE, NOT how computers work.

THAT’S why Shop Rats are better suited to be Simulation Engineers than
Computer Science Majors.

Computer Science Majors usually attempt things that are not practical in the real world, such as holding a car hood with a suction cups end-of-arm fixture, and moving it at 2000 MM/sec, which works just fine in the computer world, but fails miserably in the real world, where the AIR RESISTANCE blows the hood off the suction cups before the destination is reached.

A Shop Rat who has, for example, done Robot Programming on the Shop Floor, won’t make that mistake.

[quote ]…The Petabyte Age is different because more is different. Kilobytes were stored on floppy disks. Megabytes were stored on hard disks. Terabytes were stored in disk arrays. Petabytes are stored in the cloud. As we moved along that progression, we went from the folder analogy to the file cabinet analogy to the library analogy to — well, at petabytes we ran out of organizational analogies.

At the petabyte scale, information is not a matter of simple three- and four-dimensional taxonomy and order but of dimensionally agnostic statistics. It calls for an entirely different approach, one that requires us to lose the tether of data as something that can be visualized in its totality. It forces us to view data mathematically first and establish a context for it later. For instance, Google conquered the advertising world with nothing more than applied mathematics. It didn’t pretend to know anything about the culture and conventions of advertising — it just assumed that better data, with better analytical tools, would win the day. And Google was right…[/quote ]

http://www.wired.com/science/discoveries/magazine/16-07/pb_theory

Automotive Manufacturing now does nearly all Robotic programming using Off-Line Simulation, NIST uses Simulation, Russian Scientists are using it to clean up Chernobyl, the navy uses it to help design atomic submarines, and there are several Sim Software products that will run on laptops with good results. So extremely expensive mega-computers are not needed in most cases.

The major caveat involves GIGO.

Well-Trained and Experienced operators are required to run the software, and they need real-world experience in the things they are trying to simulate.

Freshly-graduated Computer Science majors who have never worked in the environments simulated, simply will not do.

DARPA found this to be true, and tried to get operators trained in Community Colleges using a project called "Conduit" in the late 90′s. I was the instructor on this project, but it failed due to poor management.

You don’t need PhD’s. You need Shop Rats with Associates Degrees !

Additionally, I could see business applications beyond product development in general business development. My team has recently gone through an exercise in which we selected key target geographies based on a variety of criteria including sales, growth, market size, margin, etc. We were limited by the number of variables we could handle. This solution would seem to eliminate that constraint.

While I see the potential of this sort of solution, I have trouble seeing how WELL it might translate to business solution and/or CPG product development. Development of a complex model may prove more effort than the solution would ultimately be worth given the short cycle time and lower overall price (i.e. lower risk) in this market. A super-computer may be more power than I might need.

Any thoughts on simpler applications of this solution? Could you provide an example of this tool (or one like it) being used (i.e. sample variables, sample inputs, etc) so I could better translate this into my potential needs?

Thanks,
Ward Elwood
Sr. Brand Manager, Developing & Emerging Markets
Kimberly-Clark

I think that this type of software will now put the SSDM analysis in the hands of the middle tier manufacturers. This is a good thing since it should improve products and bring about more competition in areas that typically have been the domain of larger companies. It also should bode well for the consumer who should see the effects of this type of product quality improvement in cheaper and better products.

This type of product can also benefit in other areas where it is not used as often if at all like building materials, replacement parts, safety equipment, renewable energy equipment, and healthcare.

The smaller manufacturers may have to ramp up for this type of software by dedicating some engineering resources to figure out the variables, assumptions, etc. to create a realistic model. This is the hard part. You still have to know your product and how to successfully model all the constraints.
However, this probably nothing more than hiring a couple of PhDs or consultants to help you these companies get rolling. The end result should be interesting.

High Performance Information and Choice Making focuses on the benefit for NCMS clients, rather than on a presumption of appropriate technology.

Simulation reveals the anticipated behavior of a system model. Anticipated behavior guides systems design choice-making which becomes ever more important as the system gets bigger in extent, variety and ambiguity. However, the need for High Performance (meaning high cost relative to other platforms) stems from the notion that computing is the better platform for anticipating system behavior. NCMS should focus on the Ends — Adequate, Accurate and Timely foresight about requisite system behavior — not the Means — High Performance Computing.

In fairness other kinds of platforms have not been available. However, with the advent of new processing architectures, typified by Patent Reg. # 7392229.B.2, it is now reasonable to think of a $100 chip doing the work of 3,400 microprocessors — in microseconds.

If you want to look at the question of alternatives to high performance (high cost) computers, a good overview may be seen at "The Von Neumann Syndrome", R. Hartenstein, downloaded January, 14, 2008 from
http://www.fpl.uni-kl.de/staff/hartenstein/Hartenstein-Delft-Sep2007.pdf

If you want to know more about the significance of the General Purpose Set Theoretic Processor described in Patent Reg. # 7392229.B.2 I will be happy to share a white paper regarding a Systems Viability and Verification Capabilty. Please advise.

Hope this helps move things along,

Jack Ring
Co-founder, Kennen Technologies LLC
Fellow, International Council on Systems Engineering