Standing on the beach, overlooking the bountiful, yet imperfect, harvest, he pondered the situation in front of him. “Why are all of my troop mates eating these sand-covered sweet potatoes? In the beginning, they were delicious…and without the sand. Now? these wonderful treats are all but inedible. What if I…

This is the beginning of tale based on a scientific research project, though may have evolved into something of an urban legend. The idea is that scientists in Japan, circa 1952, were studying the behaviors of an island full of macaque monkeys. At first, the scientists gave the monkeys sweet potatoes. After a period of time, the scientists then started covering the sweet potatoes in sand to observe how they would react. Not surprisingly, the monkeys still ate the treats, however begrudgingly. Then, the story goes, a young monkey took the vegetable to the water and washed it off. He discovered that it tasted as good as it did before the sand. Excitedly the young monkey showed this discovery to his mother. Approvingly, his mother began washing hers in the water as well.

Still, the vast majority still went on, crunching away on their gritty meals. Over time, a few more monkeys caught on. It wasn’t until a magic number of monkeys were doing this – we’ll say the 100th – that seemingly the entire troop of monkeys began rinsing their sweet potatoes off in the water.

Call it what you will – social validation, the tipping point, the 100th monkey effect, etc. It all comes down the idea that we may not try something new, however potentially beneficial, until it’s “OK” to do so. Cloud solutions for PLM could be coming to that point.  These products have been in the market for a few years now, and they mature with every update (and no upgrade headaches, either).

In the near future, it is forecasted that “Within the next three years, organizations have the largest plans to move data storage/data management (43%) and business/data analytics (43%) to the cloud,” as reported by IDG Enterprise in their “2016 IDG Enterprise Cloud Computing Survey.”  Another survey, “2017 State of the Cloud Survey” by Rightscale, is seeing that overall challenges to adopting cloud services have declined. One of the most important matters, security, has fallen from 29% of respondents reporting it as a concern to 25%. Security is still a valid concern, though I think the market is starting to trust the cloud more and more.

With our experience and expertise with PLM solutions in the cloud, Tata Technologies can help you chose if, when, and how a cloud solution could be right for your company. Let us know how we can help.

My last post outlined the importance of having an integrated PLM and PCM solution. Siemens PLM implements this vision though its Product Cost Management application bridging the gap between traditional PLM and ERP. With Teamcenter PCM, companies can migrate from disconnected tools to an integrated solution. The integrated IT environment platform helps them to manage cost knowledge with consistent data, build standardized obligatory cost methods and models, and create fact-based and cost-driver-transparent calculations; at the same time, it enables cross-functional collaboration and communication.

Product Costing

The highlights of product costing capabilities include Cross-functional Calculation of Pre-/Quotation Costing, Calculation of R&D Costs, Purchase Price Analysis, Open Book Accounting, Profitability Calculation/Project-ROI, Differentiated overhead calculation (freely selectable degree of detail), Process-based bottom-up calculation and cost models (cost engineering approach), Cost rate calculation with company-owned data records, Integrated cycle time calculators (die casting, injection molding, machining, MTM, client proprietary, etc.), Versioning of calculations (documented change history), Flexible simulations of what-if scenarios (e.g., production alternatives, volume adjustments), Profitability calculations (return-on-investment over product lifecycle), Flexible reporting functions (e.g., multi-stage cost driver analysis), Integration toolkits for data exchange with customer specific systems (e.g., ERP), Import and export of cost breakdown sheets (supplier and customer), Multi-lingual, multi-currency, freely configurable costing methodologies, cash flow calculation, and data management for reuse.

Tool Costing 

Teamcenter PCM’s parametric and 3D-based tool costing has support for both quotation costing in tool-making and cost analysis in tool purchasing. Tool Costing delivers fast, reliable and detailed information on manufacturing times and costs. Tool Costing also enables both buyers and tool manufacturers to precisely and repeatably understand knowledge data, secure this information within the enterprise and document it in an audit-compliant manner with the option of using 3D data for calculations. Teamcenter provides a variety of tool technologies, including injection molding, die casting, and composite tools. 3D data can be read automatically or manually to create the geometry parameters. Both the tool buyer and the tool maker – whether injection molding, die casting, cutting, stamping, or other production tools – can make decisions regarding the tool costs that are fully integrated within the Teamcenter product cost management solution.

Cost Knowledge Management 

Teamcenter PCM has a standard and extendable cost knowledge base for costing calculations including worldwide factor costs (labor, production area, energy, interest rates etc.), physical material data of all prevalent materials, reference machines with economic and technical data for all prevalent manufacturing technologies, and complete reference processes for many manufacturing methods with the ability to integrate customer specific corporate costing library.

Profitability Calculation

The integrated profitability calculation in Teamcenter gives project and product controllers and managers a powerful business case analysis and decision-making tool while delivering the necessary instruments to ensure success, including: Consolidation of multiple product(s) in a single project (general project data, lifecycle, quantity progression, unit costs and prices, etc.), year slice presentation of cash flows for project-specific investments (plants, tools, engineering, etc.), dynamization of unit costs and sales prices for the individual year slices in the product lifecycle, calculation of common profitability ratios such as net present value (NPV), internal rate of return (IRR), return on capital employed (ROCE), return on sales (ROS), amortization period (payback), project-based profit and loss accounts, as well as discounted cash flow accounts and trend curve for cumulative (discounted) cash flow, variant calculation, and sensitivity analyses for comparing various what-if scenarios and premises.

This is Part 3 in my series on the hidden intelligence of CATIA V5. To quickly recap what we have already talked about, in my first post I discussed the importance of setting up and using parameters and formulas to capture your design intent and quickly modify things that you know are likely to change. We took those principles a bit farther in my second post and discussed the value of building a design table in those situations when you may have a design with parameters that will vary and that you want to use many times. In that case you could see that we had our rectangular tubing part and could modify its wall thickness, height, and width to make several iterations of basically any size of tubing one would ever need! You would simply keeping doing a Save as… and placing those parts in your working directory to be added into an assembly at some time (I assume).

This methodology would work fine, but today I want to focus on a very cool spin on this theory by building a catalog of your most commonly used parts which are similar enough to be captured in a single model. Using our tubing model, and picking up where we left off, we have a spreadsheet that defines the parameters that change. All we would need to do to build a catalog of each iteration of the design table is add a column to the spreadsheet named PartNumber just as I have it with no spaces in the name and then associate that to the ‘Part Number’ intrinsic parameter that is created automatically when you being a model.

Let’s get started.  I will open both the model and the spreadsheet, edit the spreadsheet with the column, and then add in some part numbers.

Part numbers added

When you save the file, the field should appear in CATIA when you click on the Associations tab. […]

What is data migration and translation? Here is a definition that will help:

  • Information exists in different formats and representations. For example, Egyptian hieroglyphics are a pictorial language (representation) inscribed on stone (format)
  • However, information is only useful to a consumer in a specific format and representation. So, Roman letters printed on paper may mean the same as an equivalent hieroglyphic text, but the latter could not be understood by a English reader.
  • Migration moves data between formats – such as stone to paper
  • Translation moves data between representations – hieroglyphics to roman letters

What must a migration and translation achieve?

  • The process preserves the accuracy of the information
  • The process is consistent

In the PLM world, the requirement for data translation and migration arises as the result of multiple conditions. Examples of these include changes in technology (one CAD system to another CAD system), upgrades to software (from one level of a PLM system to later version), combination of data from two different sources (CAD files on a directory system with files in a PDM), acquisitions and mergers between companies (combine product data) and integration between systems (connect PLM to ERP).

However, migrations and translations can be fraught with problems and require considerable effort. Here are some reasons: […]

This post was originally created in January 2017.

With all the buzz about Additive Manufacturing, or 3D Printing, in the manufacturing world today, there is a lot of mystery and confusion surrounding the common practices and techniques. So, this week’s blog post will address a common type of 3D printing known as Direct Metal Laser Sintering (DMLS).

What is Direct Metal Laser Sintering?

DMLS is actually part of a broader category, commonly referred to as a Granular Based Technique. All granular-based additive manufacturing techniques start with a bed of a powdered material. A laser beam or bonding agent joins the material in a cross-section of the part. Then the platform beneath the bed of material is lowered, and a fresh layer of material is brushed over the top of the cross section. The process is then repeated until a complete part is produced. The first commercialized technique of this category is known as Selective Laser Sintering.

The Selective Laser Sintering technique was developed in the mid-1980s by Dr. Carl Deckard and Dr. Joseph Beaman and the University of Texas at Austin, under DARPA sponsorship. As a result of this, Deckard and Beaman established the DTM Corporation with the explicit purpose of manufacturing SLS machines.  In 2001, DTM was purchased by its largest competitor, 3D Systems.

DMLS is the same process as SLS, though there is an industry distinction between the two, so it is important to make note of this. DMLS is performed using a single metal, whereas SLS can be performed with a wide variety of materials, including metal mixtures (where metal is mixed with substances like polymers and ceramics).

What Are the Advantages of this Process?

[…]

When working with our customers, from time to time, we’ll get questions on why they see unexpected results in some of their searches. This typically happens when they search without wildcards (I’ll explain later). In this blog post, I hope to shed some light on what can be a confusing experience for some Vault users.

The search engine in Vault operates on a on a general computer science principle called general Tokenization. This process essentially chops up the indexed properties into chunks called tokens. When a user searches in Vault (either quick search or advanced find), the search engine will attempt to match the tokens in the search string to the tokens in the appropriate properties.  Before going further, I’ll explain how Vault does the slicing and dicing.

First, there are three categories of characters (for our purposes, at least); alpha [a-z, A-Z], numeric [0-9], and special [#^$, blank space, etc.].  Vault will parse the string and sniff out groups of characters belonging to a category.  For instance, ABC123$@# would be tokenized into 3 individual tokens:

  • ABC
  • 123
  • $@#

Again, what happened is that Vault saw the first character, A, and understood it to be an alpha character. Vault then asked “Is the next character an alpha, too?” to which the answer was yes, so the token became AB. C was then added to the initial token, as it too was an alpha character.  However, the answer was “No”, when it came to the character 1.  Vault finished its first token and began the next one, now that it sensed a different category of character. Vault continued this line of questioning with the subsequent characters.

Another example might be a file name like SS Bearing Plate-6×6.ipt. Here, we have 8 tokens:

  • SS
  • Bearing
  • Plate
  • 6
  • x
  • 6
  • ipt

Now, you may have caught the missing period. Vault will only tokenize six special characters – all others are ignored. These special special characters (sorry, had to do it) are:

  • $ (dollar sign)
  • – (dash)
  • _ (underscore)
  • @ (at symbol)
  • + (plus)
  • # (octothorpe, aka number sign)

So now where do the unexpected results come in? This usually happens when an incomplete token is used without wild cards. For example, a user wants to find a specific mounting bracket. This user then types in “mount,” expecting that to be enough. In our hypothetical Vault environment, the results would return “Fan mount.ipt” but not “Mounting bracket.ipt” like they intended. Why? Remember that Vault is trying to match exact tokens (again, without wild cards).

If the user had entered mount*, the results would return the expected “Mounting bracket.ipt” as the user intended.

Moral of the story?  Always use wild cards…always.  No, really, all the time.  For everything.

There are great engineered products and then there are commercially successful products. Many variables factor into the profitability of a product: innovation, satisfying customer needs and delivering a great customer experience with product performance help companies to drive sales, command price premiums, and boost their topline results. While product development engineers are focused on the form, fit, and function of their designs to drive innovation and a great customer experience, often the product cost impacts of their decisions to drive profitability from the expense perspective are overlooked.

Engineers seldom have visibility to the cost impact of their decisions; they can’t optimize their design parameters for cost in the context of other design parameters, as they don’t have the required information. The biggest challenge to optimizing cost is understanding different cost parameters, and that requires a detailed knowledge of manufacturing processes and cost drivers.

Product Cost Management (PCM) allows product development companies to design for cost by providing early visibility to the cost implications of design decisions. Using PCM processes and tools they can systematically simulate and evaluate different scenarios to develop an ideal “should cost” model that is based on a detail-oriented cost parameters of materials, manufacturing processes, supply chain , regulatory compliance, product support and service. This helps them to identify cost saving ideas like changing materials, simplifying designs, combining parts /functions, or changing production locations.

There are different PCM techniques. Feature-based techniques look at the characteristics of a design to eliminate unnecessary, high-cost design features. Bottoms-up approaches based on Bill of Process (BOP) calculate more accurate cost models based on the manufacturing processes including labor, equipment, tooling, setup, and other production information. It enables companies to perform a “what if” analysis by modeling multiple production scenarios.

The benefits of PCM are not only for manufacturing companies to design their products for optimal cost by receiving feedback on the cost impact of the design decisions – they also help companies that rely on their supply chain to source for optimal pricing. Even though Direct Material Sourcing processes introduce a price competition, they are seldom based on optimum cost. Using PCM, original equipment manufactures (OEMs) can simulate their suppliers’ production costs. Even if no supplier can match the ideal “should cost” price point, it allows supplier selection with the knowledge that they need OEM help to produce at the ideal cost. This again drives continuous investments towards cost improvement in the supply chain; that’s a win-win scenario for both OEMs and Suppliers.

In my next post, I will show you how PLM supports PCM.

This post was originally written in January of 2017.

With all the buzz about Additive Manufacturing, or 3D Printing, in the manufacturing world today, there is a lot of mystery and confusion surrounding common practices and techniques. This week’s blog post will address a common type of 3D printing known as Laminated Object Manufacturing (LOM).

Laminated Object Manufacturing or LOM works by joining layers of material (usually paper or plastic sheet) with an adhesive while a knife or laser cuts cross-sections to build a complete part. Parts are typically coated with a lacquer or sealer after production.

What Are the Advantages of this Process? […]

Everyone knows that a PLM journey can be a long and expensive path, with frustrations at every turn. The question an organization often asks is: is it worth trying to walk that path?

Effective and correctly implemented PLM can significantly impact several business costs, resulting in large organizational savings. Take a look at the list below and consider how your costs look right now – you may be able to answer your own question.

10 Business Costs Directly Impacted by PLM

  1. Factory Rework and Scrap. These costs can be substantial in a manufacturing organization. Not all rework and scrap is caused by insufficient or miscommunicated engineering and design, but a sizeable percentage is traceable back to this root cause. An effective PLM setup will reduce engineering-originated errors by providing timely and accurate information to the factory floor.
  2. Supplier Quality. Getting timely and accurate information to your suppliers can ensure that they deliver quality parts to your production line. PLM correctly configured can make this happen.
  3. Expedited freight costs. How many times does a product get out of your factories late? In order not to incur penalties, the shipping is expedited at a huge premium. Can any of these incidents be traced back to delayed engineering data? Then a PLM system can help.
  4. Effort to process bids. To win business, you need to respond to RFQs by preparing bids. This effort does not directly generate revenue, and so the preparation process must be as streamlined as possible. Are your key people distracted by bids? Automating the process with a PLM system will reduce the effort required.
  5. Time to create reports. Management requires reports that need to be reviewed. Are these created manually from disparate sources? Why not use a PLM system to generate these reports automatically on demand? There are huge time savings to be had from this enhancement.
  6. Time preparing data for downstream users. How much time does your valuable engineering resource spend extracting, converting, and transmitting engineering data to downstream users? Hours per week? This cost can be avoided completely by setting up a PLM system to deliver this data with no effort from the engineers.
  7. Effort to process engineering change. Your company struggles to process engineering change requests and notices. Many are late and require multiple rework cycles. A PLM can fix that by automating the process and ensuring accurate information.
  8. Cost of physical prototypes. Do you spend a lot of money on building and testing physical prototypes as part of your design process? Do you have to build them all or could some be eliminated by better engineering tools and virtual simulation? A leading-edge PLM system can reduce this dramatically.
  9. Your suppliers deliver parts that require rework. You are constantly getting incorrect parts from your suppliers. But do your suppliers have the right information to begin with? PLM technology can bridge this gap
  10. Wasted development effort. Do you spend funds developing products that go nowhere? This problem can be addressed by a PLM system that manages your development portfolio more accurately.

Do you have more than three of these costs that concern your or that are out of control? Then you definitely need to take a serious look at implementing or reworking your PLM system. We can help – just let us know.

This is an exciting post for me! Dassault has just come out with a couple of new bundles that blow the doors off anything I have seen previously.

CATMEE – Mechanical Engineering Excellence

The first package is named CATMEE; this would be the “Mechanical” version of the package. In Classic terms, previously for this purpose I would have recommended an MD2 trigram.  In PLM Express bundles, I would have recommended a CAC+MCE bundle to these types of users. They are typically heavy on the mechanical solid modeling portion of CATIA, and do not do very much surfacing.  CATMEE is a CAC+MCE on steroids! It includes CAT3DX (which I talked more about in my last post) AND also includes bundles for FPE (Fabricated Product), JTE (Jig and Tool Creation), PRX (Animated Product Review), FTX (3D Master), and TRE (Technical Specifications Review).

CATMEE Package Bundle

I realize that this sounds like a bunch of trigram soup. What does it really mean in CATIA V5? Well from a workbench standpoint, the CAC+MCE add-on looks like this:

CAC+MCE Workbenches

From a workbench standpoint, CATMEE looks like this:

CATMEE Bundle Workbenches

Take a closer look: you get Sheet Metal, 3D GD&T functionality (the good one, FTA!), Mold Tooling, Structure Design, and also DMU! In fact Kinematics, Space Analysis and Fitting Simulation alone can get expensive as an add-on, but here it comes with the bundle. Imagine cutting a section and it actually still being there when you click OK, and being available in the specification tree and updates when you change your part, as well as clearance checks, interference checks, etc.  MD2 and/or CAC+MCE users know exactly what I am talking about!

If you are in the market for a new seat or two this year and you are a mechanical customer, you should talk to your account manager and ask about this package; the new configurations not only help your productivity, but also help you expand your capabilities of what kinds of parts and markets you can get into.

CATMSE – Mechanical and Shape Engineering Excellence

This package is where you will really get your bang for the buck! CATMSE is a package we would have previously bundled as either an HD2 (Classic) or CAC+MCE+HDX (PLM Express). It is designed more for the mechanical and surfacing (Hybrid) type of role as a designer. Traditionally CAC+MCE+HDX overall gave you the GSD version of the Generative Shape Design workbench (better sweep functions, laws, etc) as well as a DL1 (Developed Shapes Toolbar in GSD) and a light version of Freestyle workbench (FS1). […]

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