PLM
CIM data defines PLM as:
• A strategic business approach that applies a consistent set of business solutions that support the collaborative creation, management, dissemination, and use of product definition information
• Supporting the extended enterprise (customers, design and supply partners, etc.)
• Spanning from concept to end of life of a product or plant
• Integrating people, processes, business systems, and information
Three core or fundamental concepts of PLM are:
• Universal, secure, managed access and use of product definition information
• Maintaining the integrity of that product definition and related information throughout the life of the product or plant
• Managing and maintaining business processes used to create, manage, disseminate, share and use the information.
PATH TO PLM
• PLM uses product information, computers, software, and simulations to produce the first product as efficiently and as productively as the last product throughout the design, development, and delivery process.
•Lean manufacturing-considerable resources - equipment to be reconfigured, machines rearranged, and material relocated. Once the system is set in place, PLM uses little resources, since this same process is done digitally.
•The most efficiently produced product -from the best lean manufacturing processes can be flawed as a result of design failure or failure in actual use. - efficiently produced scrap that is a waste of time, energy, and material.
Lean Thinking- Globally
• The bigger opportunity is to use PLM to enable better information flow across the entire organization.
• PLM holds the promise of improving productivity through a cross functional approach, using product information.
•PLM is that it does not improve efficiency and productivity from simply a cost-reduction perspective but also from a revenue perspective. In past CEO/CIO to board of directors: “Give us $500 million and two years, and we'll give you an enterprise system" are gone—now the only way to get approval is with well defined ROI.
•PLM-The premises we will discuss are: information as a substitute for time, energy, and material; the trajectory of computer technology development; the virtualization of physical object; and the distinction between processes and practices.

Information - substitute time, energy, material
• Misconception - information often is taken for granted. While it is cheaper to move informational bits than physical atoms, information is neither costless nor, is especially cheap. This is very different from the assumption that the information needed to replace the time, energy, and material used inefficiently is less expensive than simply wasting that time, energy, and material.
•The driver for this cost decrease is not simply the doubling of production. Management and workers develop information based on their experience in producing the products, they are able to substitute that information for the inefficient use of time, energy, and material.

Information production cost

•Production costs decrease with the number of units produced
Figure an example of an 80 percent learning curve. For every doubling of production units (1X, 2X, 3X, etc.), costs decrease by 20 percent.

The Trajectory of Computer Technology Development
•PLM may be the most Information Technology (IT) resource intensive general purpose application.
•The math-based representations of PLM product information require substantial computing capabilities ( also required to render visual representations of the math-based data and manipulation)
•Moore's Law - almost 40 years ago by Gordon Moor- founder Intel, Computing capability of the microprocessor would double every 18 months. Since 1971 the number of transistors on a processor increased from 2,250 on the first Intel microprocessor, called the 4004, to 1.7 billion transistors on the new Intel Montecito processor
•In addition-corresponding increases in storage and bandwidth. Storage double every 12 months. Internet capabilities also doubles every 12 months or less.
•Supercomputers-are capable of millions of calculations per second.
•Extremely expensive — the fastest supercomputer of 2008, IBM’s Road Runner, costs $120 million — 1.042 petaflops
•May 2010 the Cray Jaguar is the fastest supercomputer in the world. - With a peak speed of 2.33 petaflops (over two thousand trillion calculations per second), 2011 "K" supercomputer by Fujitsu and RIKEN 10.51 petaflops
•Access to them is limited.
•A smaller versions, like typical desktop PC, are becoming a hit among researchers for massive processing power
•Demand personal supercomputers grew at an average of 20% percent every year between 2003 and 2008 (research firm IDC)
Why GPU speed are slower them CPU speed? 700Mhz versus 3000Mhz.
1. Those 700 Mhz are dedicated to doing one thing only - 3D processing.
2. They have their own dedicated memory which is on the same PCB (printed circuit board) as the GPU, therefore it has direct access to the memory. Compared to the distance between the RAM slots which your CPU uses, the distance between the GPU and its RAM is much smaller which makes a lot of difference when it comes down to access time.
3. The RAM on video cards is getting faster and faster than system memory. Example - current GPUs use GDDR3 while Intel's maps show that they will start using DDR3 for system memory in 2007.
4. Interrupts are another reason why GPUs don't need speeds that great. The CPU is interrupted by lots of things - every keystroke on your keyboard, your audio card if it is integrated in your motherboard, etc. In comparison, the GPU is not, so it does not have to share its computing power with anything else.
Graphic chips like the Nvidia G8800 have about 520GFLOPS of performance.
Some have been adapted for more general processing using the C language and are being banded together for supercomputers with 2-40 times the performance of regular CPUs.
Wired magazine -array of 536 GPUs significantly outperformed some 17,485
CPUs from Linux boxes. The 536 GPUs producing 35 trillion calculations per second compared to 21 trillion calculations per second for the CPUs.
The UNC Chapel Hill Gamma Research Team -Nvidia 7900 GTX GPU up against two different leading-edge optimized CPU-based implementations running on high-end, dual-3.6-GHz Intel Xeon processors or dual AMD Opteron 280 processors. -The results -GPU performed at anywhere from 2 to 5 times the speed of the CPU-based systems on these specific applications. standard numeric-based computational algorithms, including sorting, FFT (Fast Fourier transform) and matrix multiplications.
REF: http://www.theinquirer.net/inquirer/news/1049494/nvidia-s-tesla-is-desktop-supercomputer
Gamma group-Ming C. Lin develop many new GPU-based technologies for physics simulation -- including collision detection, motion planning and deformable simulations – speeds increasing up to 10 to 20 times beyond previous methods. REF: http://nextbigfuture.com/2006/11/gpu-supercomputers.html

•Our VR capabilities is limited tied to simple objects. We can do it for a coffee cup. We cannot do it for it for all the parts of an automobile. The second is that this virtualization cannot be shared with anyone else. This virtualization occurs in our individual, unshareable minds. We can try and describe the image we would like others to virtualize, but have little confidence in our images being the same as theirs. In order to have everyone have the same image of a physical object. we need to have some sort of physical representation for all to see.
•Performance test-VR+VR environment- if the tested object cannot be distinguished form the actual –it is successful.
•PLM substitute information –test for performance to imitate the actions of the physical world. (examples-EON demo) http://generationdreamteam.free.fr/Quizz.html http://generationdreamteam.free.fr/gthdcompa2.html http://generationdreamteam.free.fr/getawaycompa.html