Is KBE Necessary?

One can look at the question of the title by asking another question which involves a similar but simpler problem. Is computing necessary?

Ignoring several issues, one can take ‘computing’ to mean that collection of elements that supports PLM/CAx ^[1]; then, one can demonstrate that the collection does provide the support. Essentially, we do this type of thing every day, and we all know that the successful evolution of PLM/CAx as depicted in Figure 1 was largely due to advances in computation.

But, there was much more involved than just computing. During the time period, engineering disciplines improved both in foundational knowledge and in the fundamentals of practice. There were improvements in GUI technology, operating system capability, application development methods, and a lot more.

Figure 1: PLM/CAx, Computing

In short then, the ‘necessary’ question with regard to ‘computing’ is obviously true.

Now, we can turn the necessary question around and ask another of computing. ‘Is computing sufficient?’ In the progressive movement shown in Figure 1, one can answer the sufficiency question for computing somewhat like the following:

• Engineering would say ‘no’ as there are many more factors that pushed the progress that we have seen and that many of these factors relate to human attributes, such as creativity and ability;
• Yet, a particular management view may want to say ‘yes’ in a push for greater automation and in the pursuit of the power of computing.

Before moving on, a brief look at ‘necessary’ and ‘sufficient’ is in order. Hopefully, this discussion will show the importance of these simple concepts in the management of complicated systems and apply them to the KBE questions.

What are ‘necessary’ and ‘sufficient’ exactly ^[2], how do they apply, and ought we to care?

• A ‘necessary’ item can be thought of as a pre-requisite, in the sense that the absence of the necessary item, or equivalently its falsity, guarantees failure. So, if B is necessary for A, then B needs to be true for A to be true. A simple biological example would take A for life and B for air. If there is no air (B), then there is no life (A) (using ‘biological’ as we know it, generally).
• A ‘sufficient’ item can be thought of as an assurance. That is, if A is sufficient for B, then the presence of A guarantees B. Taking the above biological example, if A (life) is present, then we know that there is B (air). Something being alive implies air.

Now these relationships do not consider quality or degree of life or air. Not that the two concepts are not apropos in such analysis. In a sense, such concerns are going to be seen a central to the issues of KBE and its roles, including how to handle ambiguity, uncertainty, and other problematics.

In diagrams, given A = life and B = air, then we have the following.

Necessary: A <= B
Sufficient: A => B

Keeping in line with the PLM/CAx theme, the following discussion will use the relationship between a square and a rectangle. Not only can this example be extended to higher-dimensional objects, one can apply the concepts to logic as encapsulated in the computational framework, including those represented by KBE and any other advanced technique.

We all know the square; in this context, there are two main things about the square that are of interest. First, it is a rectangle. Second, it has equal sides. We could probably think of other attributes, but these two are the important ones that we need to consider. For instance, we don’t care about the square’s color or how the square’s sides are drawn.

Now, the rectangle is a necessary condition for the square; though, it is not the only one. We could look at this in terms of the class framework found in object-oriented modeling. To build a rectangle, one would collect, and join, straight lines that are 4 in cardinality and that are aligned such that they are orthogonal at the joins. Taking this a little further, one can say that 4 sides and equal angles at the join are necessary for the rectangle. Then, when an equal-sides condition is imposed on our rectangle object, we have the square.

In short, we have the following which describes the necessary conditions of the transitive relationship between the square and the rectangle.

rectangle <= 4-sides + equal-angles
square <= rectangle + equal-sides

If we turn the above around, we can look at the ‘sufficient’ side. If we know that we have a square, then we know that we have a rectangle, too. If we know we have a rectangle, then we know about four sides and 90 degree angles. From the information side, we know more starting at square than at rectangle.

So, why ought we to care? Problem solving deals with deft handling of the necessary and sufficient. For instance, a Pareto chart, in many cases, depicts a ranked set of necessary conditions (factors). It is not uncommon for a collection of factors that have the larger impact of a set of factors to be collected and tagged as being sufficient. Of course, ignoring the lesser factors can have risks with this type of closure.

Yet, such simplification, or knowledge refactoring in some senses, is just what smart problem solving requires. Example, many situations have shown that mitigating the risks of eliminating the lower-order necessary factors can work, such as when we see jobs disappear when the human element is deemed as not necessary. Further, many times a necessary set that has been reduced can become thought of as sufficient, thereby resulting in too strong assumptions being applied without the proper means to really evaluate risk. KBE plays a role in managing this, assuming that KBE is properly applied.

The type of transitive operation that we just saw is the basis for advanced computing, as a system involves sets of large cardinality and the relationships of members of these sets. Unfortunately, the relationships and their dealings can get embedded in a computer language and might become less available to the user than desirable. Again, one symptom is unclear understanding of assumptions. Not being able to adequately handle the analytics related to the necessary and the sufficient can be problematic.

As discussed above, we have the following diagram for the necessary set behind the PLM/CAx’s current success.

PLM/CAx <= ‘computing’ + ‘knowledge’ + ‘GUI’ + ‘…’

The use of ‘…’ suggests that there are many other necessary conditions required for the current state of PLM/CAx that need to be considered. Wikipedia ^[1] provides a graphical view of the many, necessary pieces of PLM/CAx. Of course, ‘knowledge’ as used previously would include KBE and other elements.

So, we see that computing is a large collection of necessary entities. Implementation, the concept used for providing a computer-based solution, is a subset of those possible collections that meet requirements, certain test criteria, and good test results. Together these are part of the necessary mix. None of these necessary conditions are sufficient in themselves. Yet, managing the necessary is one of the characteristics of smart work.

Now, having looked at the ‘computing’ necessary question, how does one answer the same question for KBE? That is, is KBE necessary?

The question presupposes that we have a definition for KBE ^[3] and how it differs from automation. ^[4] We can talk about two types, for now, with the demarcation of the millennium as the main dividing line, namely the KBEs of the 20^th and the 21^st centuries. Though these two differ in many areas, there is a commonality between the two that might need further attention as some union across the two could unleash computational power.

• The 20^th century KBE came out of the AI realm and used the Lisp environment on Unix. ^[3] Even AI has its definitional problems; essentially, AI is what we haven’t figured out yet. Given its basis, 20^th century KBE had a formidable mixture of necessary elements that demonstrated measurable gains to those who applied the technology. Since the 20^th century KBE had such a long timeline, its collection lagged the general industry advancements in several aspects.

Hence, the 20^th century collection was not ‘sufficient’ where the label of ‘insufficiency’ is not used pejoratively. In the evolution of computing as depicted in Figure 1, the existence of a gap between sufficiency goals and analytical insufficiency is the impetus for improvement.

• What has emerged in the 21^st century is a newer collection of necessary elements based on more modern methods which are in several cases more mature than what was available to the 20^th century system. The newer interfaces are GUI (iconic) with a heavy graphical emphasis, such as that demonstrated in ‘Realistic Simulation’ shown in Figure 1. There are improved means to handle parameters and to model relationships. Too, there is a modern object-oriented framework available for the user.

Then, there are improved representations of physical entities that are the basis for products that use PLM/CAx’s methods. The intermediate models that are necessary for managing ‘meta’ information are growing more complicated and non-intuitive. The industry has devoted much effort to improving the interface between the abstract models and what the human can understand. PLM/CAx’s large scope is the example for our domains.

Another commonality was that success relied upon human involvement. In terms of the former, the system essentially allowed computationally hard spaces to be traversed and exploited by enabling a ‘man-in-the-loop’ scheme. In terms of the latter, such interface issues are still open and, quite possibly, are the prime focus required for the next step.

In both cases, KBE tries to correct some computing limitations by starting with an extensive parametric overlay and by allowing programmatic changes by the user. ^[5] In a sense, KBE allows us a means to describe and manage minimal necessity sets. One management scheme would involve decisions related to relaxing a sufficiency closure when we need to re-look at necessary conditions. There needs to be continuing efforts to understand the 20^th century KBE framework so as to identify ‘necessary’ elements that ought to carry to the 21^st century. An example would be the expressive power exhibited by those doing end-user computing ^[6] in the 20th century KBE environment.

So, many see KBE as necessary in the PLM/CAx mix; but looking at the importance of analyzing necessary conditions also suggests what KBE brings in terms of its required focus. Those interested in KBE have discussed whether there is a generic viewpoint that could be defined as the basis for bolstering the 21^st century KBE. ^[5] We need to look further at requirements and methods, in terms of architecture, parametrics, relationships, temporal modeling, optimization, decisions, work flow (temporal), and much more.

This framework and related issues will be further discussed at the COE Meeting in Las Vegas.

[1] “Product Life Cycle Management” Wikipedia (the free Encyclopedia)
[2] “Necessary and sufficient conditions” Wikipedia (the free Encyclopedia)
[3] “Knowledge Based Engineering” Wikipedia (the free Encyclopedia)
[4] Brian Prasad “What distinguishes KBE from Automation" COE NewsNet, June 2005
[5] John Switlik “How Paradigms of Computing might relate to KBE" COE NewsNet, Winter 2007
[6] “End User Computing” Wikipedia (the free Encyclopedia)

To contact the author, use john.m.switlik@ieee.org.

Proficiency Empowers Manufacturers and Suppliers with CAD Product Knowledge Integration While Protecting Intellectual Property

Proficiency, Inc., based in Massachusetts, is the leading developer of solutions that enable manufacturers and their suppliers to extract and share implicit product knowledge from diverse engineering and manufacturing environments.

Proficiency has been the innovator in product knowledge integration and engineering collaboration since 1998. Companies in the automotive, aerospace & defense, and heavy machinery industries such as Ford Motor Company, Boeing, European Aeronautic Defense & Space Company(EADS), and Bombardier, Inc. use Proficiency’s Collaboration Gateway^tm in their heterogeneous PLM and multi-CAD environments to ensure effective Product Knowledge Integration (PKI) during design and manufacturing processes. The solution significantly reduces cost, risks, and errors while improving profitability by shortening delivery times, promoting re-use and protecting intellectual property (IP) assets during collaboration.

Proficiency provides complete solutions for CAD migrations to suppliers delivering product knowledge to their OEMs and partners sharing product knowledge. The inability to efficiently and effectively share product design information between designers, design teams and with manufacturing is a longstanding and well-documented problem. Manufacturers who view and address Product Knowledge Integration as a strategic business initiative will find themselves with a significant competitive advantage through lowers costs, faster time-to-market, better quality and more time for product innovation.

Collaboration Gateway
The company’s flagship product, Collaboration Gateway^tm, uses patented technology to automatically extract product knowledge from a source system, such as a 3D CAD system, and convert the model to the Universal Product Representation (UPR). This extensible format represents the complete product definition including features, parameters, history, manufacturing attributes, metadata, assembly information and associative properties. Once stored in the UPR format, it can be moved into other formats including major CAD system formats, such as CATIA V4 and CATIA V5.
IP Protection and Control the Collaboration Gateway includes programmatic control of the type of product design knowledge that is imported and exported, providing complete intellectual property (IP) protection. A process template provides multiple levels of control and granularity of design information, such as feature definition and history to be exchanged. Source data, complete with feature history, can be visualized to determine the robustness of models to be exchanged without requiring access to the authoring CAD system.

Product Knowledge Integration – Full Service Solution
Proficiency offers a combination of methodology and technology to define robust, predictable, repeatable processes, which can suit different business cases from migrations of Gigabytes to Terabytes, or delivery of critical production data from supplier to OEM or partner to partner.

The company offers a full service solution, including expert support for internal resources or certified service providers as needed.

In addition to the automated product knowledge integrations, Collaboration Gateway^TM provides extensive reporting, including validation and transaction records. When used as part of the design process, the reports allow design teams to understand issues related to their data capture practices, such as what modeling techniques and features are most or least portable, robust or standard.

Product Lifecycle Management (PLM) Integration
The Proficiency solution can be integrated with existing PDM & PLM implementations. In the simplest form, integration can provide automatic conversions to selected formats controlled by the PLM system’s business logic. In deeper implementations, it can serve as a means to populate, validate or reconcile PLM metadata with CAD model or drawing information. The Gateway can be integrated into most popular PLM solutions.

Leveraging advanced tools such as the Collaboration Gateway clearly solves the issues associated with diverse CAD and PLM systems, enabling OEMs & suppliers to effectively share complex product knowledge.

###

For more information on Proficiency, please visit www.proficiency.com
or request a call from one of our representatives to learn more by emailing us at:
sales@proficency.com or calling in the U.S. 508-475-0470 or in Europe +49 0811555260

Proficiency Announces Comprehensive CATIA V4 to V5 Solution

Proficiency’s new release of Collaboration Gateway™ version 6.0 offers manufacturers a unique solution for CAD Product Knowledge Integration (PKI). Proficiency provides solutions for migration, supplier delivery and partner delivery. In this new version a comprehensive package for migration from CATIA V4 to V5 was introduced that enables significant cost reductions, and improved quality.

As compared to traditional translators, which offer only geometry, limited feature support and no record of what was exchanged, Collaboration Gateway provides the best of all applications. Both precise geometry and features can be exchanged, enabling the exchange of design intelligence such as: sketches, dimensions, features, PMI, geometry, and assemblies.

The impact of the Collaboration Gateway - based solution is similar to Six Sigma processes: it reduces the variability of the process, increases reliability and output quality.

Among its capabilities are many decision support tools to ensure a predictable process:

• Source Model Analysis – to detect any source data inconsistency.
• Feature Mapping – to provide in-depth reporting for the rebuild of the product knowledge
• Quality Validation Reports – automatic alerts for features, parts and assembly deviations to minimize lost of product knowledge.

Figure 1: Feature mapping

The Process audit is implemented by an in-depth reports of “what” exchanged and “how.” (Figure1). It gives users confidence that a migrated assembly is both accurate and modifiable. The reports also provide certified service providers and users with the information required to quickly modify a design.

Figure 2: Quality Report

This package was designed to accommodate the challenge of preserving the knowledge investment while moving to the new environment (Figure 2). It ensures smooth and systematic transition and is suitable for migrations of hundreds of Gbytes of critical production data.

The migration solution between CATIA V4 to CATIA V5 provides a turnkey solution for all the different design methodologies used in CATIA V4, including top-down design,  Multi-Model Link, associative 2D drawings and constraints at all levels (Figure3).

Figure 3: Multi-Model Link

In addition, it provides a solution for the coexistence of CATIA V4 and V5 by handling hybrid models that includes both V5 CATParts and CATIA V4 Model files.

Proficiency consultants can help design a cost-effective and fast migration process whether users need to migrate Gbytes or Tbytes of data. Complete Product Knowledge Integration also can be accomplished in multi-CAD environments, including ProE, NX and I-deas.

About Proficiency:
Proficiency, Inc., based in Massachusetts, is the leading developer of solutions that enable manufacturers and their suppliers to extract and share implicit product knowledge from diverse engineering and manufacturing environments.

Global enterprises in the automotive, aerospace & defense, and heavy machinery industries such as Ford Motor Company, Boeing, European Aeronautic Defense & Space Company, and Bombardier, Inc. use Proficiency’s Collaboration Gateway  in their heterogeneous PLM and multi-CAD environments to ensure effective product knowledge integration (PKI) during design and manufacturing processes. The solution significantly reduces cost, risks, and errors while improving profitability by shortening delivery times, promoting re-use and protecting intellectual property (IP) assets during collaboration.