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In my earlier post The weekend after PDT Europe I wrote about the first day of this interesting conference. We ended that day with some food for thought related to a bimodal PLM approach. Now I will take you through the highlights of day 2.
Interoperability and openness in the air (aerospace)
I believe Airbus and Boeing are one of the most challenged companies when it comes to PLM. They have to cope with their stakeholders and massive amount of suppliers involved, constrained by a strong focus on safety and quality. And as airplanes have a long lifetime, the need to keep data accessible and available for over 75 years are massive challenges. The morning was opened by presentations from Anders Romare (Airbus) and Brian Chiesi (Boeing) where they confirmed they could switch the presenter´s role between them as the situations in Airbus and Boeing are so alike.
Anders Romare started with a presentation called: Digital Transformation through an e2e PLM backbone, where he explained the concept of extracting data from the various silo systems in the company (CRM, PLM, MES, ERP) to make data available across the enterprise. In particular in their business transformation towards digital capabilities Airbus needed and created a new architecture on top of the existing business systems, focusing on data (“Data is the new oil”).
In order to meet a data-driven environment, Airbus extracts and normalizes data from their business systems and provides a data lake with integrated data on top of which various apps can run to offer digital services to existing and new stakeholders on any type of device. The data-driven environment allows people to have information in context and almost real-time available to make right decisions. Currently, these apps run on top of this data layer.
Now imagine information captured by these apps could be stored or directed back in the original architecture supporting the standard processes. This would be a real example of the bimodal approach as discussed on day 1. As a closing remark Anders also stated that three years ago digital transformation was not really visible at Airbus, now it is a must.
Next Brian Chiesi from Boeing talked about Data Standards: A strategic lever for Boeing Commercial Airplanes. Brian talked about the complex landscape at Boeing. 2500 Applications / 5000 Servers / 900 changes annually (3 per day) impacting 40.000 users. There is a lot of data replication because many systems need their own proprietary format. Brian estimated that if 12 copies exist now, in the ideal world 2 or 3 will do. Brian presented a similar future concept as Airbus, where the traditional business systems (Systems Engineering, PLM, MRP, ERP, MES) are all connected through a service backbone. This new architecture is needed to address modern technology capabilities (social / mobile / analytics / cloud /IoT / Automation / ,,)
Interesting part of this architecture is that Boeing aims to exchange data with the outside world (customers / regulatory/supply chain /analytics / manufacturing) through industry standard interfaces to have an optimal flow of information. Standardization would lead to a reduction of customized applications, minimize costs of integration and migration, break the obsolescence cycle and enable future technologies. Brian knows that companies need to pull for standards, vendors will deliver. Boeing will be pushing for standards in their contracts and will actively work together with five major Aerospace & Defense companies to define required PLM capabilities and have a unified voice to PLM solutions providers.
My conclusion on these to Aerospace giants is they express the need to adapt to move to modern digital businesses, no longer the linear approach from the classic airplane programs. Incremental innovation in various domains is the future. The existing systems need to be there to support their current fleet for many, many years to come. The new data-driven layer needs to be connected through normalization and standardization of data. For the future focus on standards is a must.
Simon Floyd from Microsoft talked about The Impact of Digital Transformation in the Manufacturing Enterprise where he talked us through Digital Transformation, IoT, and analytics in the product lifecycle, clarified by examples from the Rolls Royce turbine engine. A good and compelling story which could be used by any vendor explaining digital transformation and the relation to IoT. Next, Simon walked through the Microsoft portfolio and solution components to support a modern digital enterprise based on various platform services. At the end, Simon articulated how for example ShareAspace based on Microsoft infrastructure and technology can be an interface between various PLM environments through the product lifecycle.
Simon’s presentation was followed by a panel discussion where the theme was: When is history and legacy an asset and barriers of entry and When does it become a burden and an invitation to future competitors.
Mark Halpern (Gartner) mentioned here again the bimodal thinking. Aras is bimodal. The classical PLM vendors running in mode 1 will not change radically and the new vendors, the mode 2 types will need time to create credibility. Other companies mentioned here PropelPLM (PLM on Salesforce platform) or OnShape will battle the next five years to become significant and might disrupt.
Simon Floyd(Microsoft) mentioned that in order to keep innovation within Microsoft, they allow for startups within in the company, with no constraints in the beginning to Microsoft. This to keep disruption inside you company instead of being disrupted from outside. Another point mentioned was that Tesla did not want to wait till COTS software would be available for their product development and support platform. Therefore they develop parts themselves. Are we going back to the early days of IT ?
Interesting trend I believe too, in case the building blocks for such solution architecture are based on open (standardized ?) services.
After the lunch, the conference was split in three streams where I was participating in the “Creating and managing information quality stream.” As I discussed in my presentation from day 1, there is a need for accurate data, starting a.s.a.p. as the future of our businesses will run on data as we learned from all speakers (and this is not a secret – still many companies do not act).
In the context of data quality, Jean Brange from Boost presented the ISO 8000 framework for data and information quality management. This standard is now under development and will help companies to address their digital needs. The challenge of data quality is that we need to store data with the right syntax and semantic to be used and in addition, it needs to be pragmatic: what are we going to store that will have value. And then the challenge of evaluating the content. Empty fields can be discovered, however, how do you qualify the quality of field with a value. The ISO 8000 framework is a framework, like ISO 9000 (product quality) that allow companies to work in a methodological way towards acceptable and needed data quality.
Magnus Färneland from Eurostep addressed the topic of data quality and the foundation for automation based on the latest developments done by Eurostep on top of their already rich PLCS data model. The PLCS data model is an impressive model as it already supports all facets of product lifecycle from design, through development and operations. By introducing soft typing, EuroStep allows a more detailed tuning of the data model to ensure configuration management. When at which stage of the lifecycle is certain information required (and becomes mandatory) ? Consistent data quality enforced through business process logic.
The conference ended with Marc Halpern making a plea for Take Control of Your Product Data or Lose Control of Your Revenue, where Marc painted the future (horror) scenario that due to digital transformation the real “big fish” will be the digital business ecosystem owner and that once you are locked in with a vendor, these vendors can uplift their prices to save their own business without any respect for your company’s business model. Marc gave some examples where some vendor raised prices with the subscription model up to 40 %. Therefore even when you are just closing a new agreement with a vendor, you should negotiate a price guarantee and a certain bandwidth for increase. And on top of that you should prepare an exit strategy – prepare data for migration and have backups using standards. Marc gave some examples of billions extra cost related to data quality and loss. It can hurt !! Finally, Marc ended with recommendations for master data management and quality as a needed company strategy.
Gerard Litjens from CIMdata as closing speaker gave a very comprehensive overview of The Internet of Thing – What does it mean for PLM ? based on CIMdata’ s vision. As all vendors in this space explain the relation between IoT and PLM differently, it was a good presentation to be used as a base for the discussion: how does IoT influence our PLM landscape. Because of the length of this blog post, I will not further go into these details – it is worth obtaining this overview.
Concluding: PDT2016 is a crucial PLM conference for people who are interested in the details of PLM. Other conferences might address high-level customer stories, at PDT2016 it is about the details and sharing the advantages of using standards. Standards are crucial for a data-driven environment where business platforms with all their constraints will be the future. And I saw more and more companies are working with standards in a pragmatic manner, observing the benefits and pushing for more data standards – it is not just theory.
See you next year ?
In my series describing the best practices related to a (PLM) data model, I described the general principles, the need for products and parts, the relation between CAD documents and the EBOM, the topic of classification and now the sensitive relation between EBOM and MBOM.
First some statements to set the scene:
- The EBOM represents the engineering (design) view of a product, structured in a way that it represents the multidisciplinary view of the functional definition of the product. The EBOM combined with its related specification documents, models, drawings, annotations should give a 100 % clear definition of the product.
- The MBOM represents the manufacturing view of a product, structured in a way that represents the way the product is manufactured. This structure is most of the time not the same as the EBOM, due to the manufacturing process and purchasing of parts.
A (very) simplified picture illustrating the difference between an EBOM and a MBOM. If the Car was a diesel there would be also embedded software in both BOMs (currently hidden)
For many years, the ERP systems have claimed ownership of the MBOM for two reasons
- Historically the MBOM was the starting point for production. Where the engineering department often worked with a set of tools, the ERP system was the system where data was connected and used to have a manufacturing plan and real-time execution
- To accommodate a more advanced integration with PDM systems, ERP vendors began to offer an EBOM capability also in their system as PDM systems often worked around the EBOM.
These two approaches made it hard to implement “real” PLM where (BOM) data is flowing through an organization instead of stored in a single system.
By claiming ownership of the BOM by ERP, some problems came up:
- A disconnect between the iterative engineering domain and the execution driven ERP domain. The EBOM is under continuous change (unless you have a simple or the ultimate product) and these changes are all related to upstream information, specifications, requirements, engineering changes and design changes. An ERP system is not intended for handling iterative processes, therefore forcing the user to work in a complex environment or trying to fix the issue through heavy customization on the ERP side.
- Global manufacturing and outsourced manufacturing introduced a new challenge for ERP-centric implementations. This would require all manufacturing sites also the outsourced manufacturers the same capabilities to transfer an EBOM into a local MBOM. And how do you capitalize the IP from your products when information is handled in a dispersed environment?
The solution to this problem is to extend your PDM implementation towards a “real” PLM implementation providing the support for EBOM, MBOM, and potential plant specific MBOM. All in a single system / user-experience designed to manage change and to allow all users to work in a global collaborative way around the product. MBOM information then will then be pushed when needed to the (local) ERP system, managing the execution.
Note 1: Pushing the MBOM to ERP does not mean a one-time big bang. When manufacturing parts are defined and sourced, there will already be a part definition in the ERP system too, as logistical information must come from ERP. The final push to ERP is, therefore, more a release to ERP combined with execution information (when / related to which order).
In this scenario, the MBOM will be already in ERP containing engineering data complemented with manufacturing data. Therefore from the PLM side we talk more about sharing BOM information instead of owning. Certain disciplines have the responsibility for particular properties of the BOM, but no single ownership.
Note 2: The whole concept of EBOM and MBOM makes only sense if you have to deliver repetitive products. For a one-off product, more a project, the engineering process will have the manufacturing already in mind. No need for a transition between EBOM and MBOM, it would only slow down the delivery.
Now let´s look at some EBOM-MBOM specifics
EBOM phantom assemblies
When extracting an EBOM directly from a 3D CAD structure, there might be subassemblies in the EBOM due to a logical grouping of certain items. You do not want to see these phantom assemblies in the MBOM as they only complicate the structuring of the MBOM or lead to phantom activities. In an EBOM-MBOM transition these phantom assemblies should disappear and the underlying end items should be linked to the higher level.
In the EBOM, there might be materials like a rubber tube with a certain length, a strip with a certain length, etc. These materials cannot be purchased in these exact dimensions. Part of the EBOM to MBOM transition is to translate these EBOM items (specifying the exact material) into purchasable MBOM items combined with a fitting operation.
EBOM end-items (make)
For make end-items, there are usually approved manufacturers defined and it is desirable to have multiple manufacturers (certified through the AML) for make end-items, depending on cost, capacity and where the product needs to be manufactured. Therefore, a make end-item in the EBOM will not appear in a resolved MBOM.
EBOM end-items (buy)
For buy end-items, there is usually a combination of approved manufacturers (AML) combined with approved vendors (AVL). The approved manufacturers are defined by engineering, based on part specifications. Approved vendors are defined by manufacturing combined with purchasing based on the approved manufacturers and logistical or commercial conditions
Are EBOM items and MBOM items different?
There is a debate if EBOM items should/could appear in an MBOM or that EBOM items are only in the EBOM and connected to resolved items in the MBOM. Based on the previous descriptions of the various EBOM items, you can conclude that a resolved MBOM does not contain EBOM items anymore in case of multiple sourcing. Only when you have a single manufacturer for an EBOM item, the EBOM item could appear in the MBOM. Perhaps this is current in your company, but will this stay the same in the future?
It is up to your business process and type of product which direction you choose. Coming back to one-off products, here is does not make sense to have multiple manufacturers. In that case, you will see that the EBOM item behaves at the same time as an MBOM item.
What about part numbering?
Luckily I reached the 1000 words so let´s be short on this debate. In case you want an automated flow of information between PLM and ERP, it is important that shared data is connected through a unique identifier.
Automation does no need intelligent numbering. Therefore giving parts in the PLM system and the ERP system a unique, meaningless number you ensure guaranteed digital connectivity.
If you want to have additional attributes on the PLM or ERP side that describe the part with a number relevant for human identification on the engineering side or later at the manufacturing side (labeling), this all can be solved.
An interesting result of this approach is that a revision of a part is no longer visible on the ERP side (unless you insist). Each version of the MBOM parts is pointing to a unique version of an MBOM part in ERP, providing an error free sharing of data.
Life can be simple if you generalize and if there was no past, no legacy and no ownership of data thinking. The transition of EBOM to MBOM is the crucial point where the real PLM vision is applied. If there is no data sharing on MBOM level, there are two silos, the characteristic of the old linear past.
(See also: From a linear world to a circular and fast)
What do you think? Is more complexity needed?
I will be soon discussing these topics at the PDT2015 in Stockholm on October 13-14. Will you be there ?
And for Dutch/Belgium readers – October 8th in Bunnik:
Op 8 oktober ben ik op het BIM Open 2015 Congres in Bunnik waar ik de overeenkomsten tussen PLM en BIM zal bespreken en wat de constructie industrie kan leren van PLM
In my previous post describing the various facets of the EBOM, I mentioned several times classification as an important topic related to the PLM data model. Classification is crucial to support people to reuse information and, in addition, there are business processes that are only relevant for a particular class of information, so it is not only related to search/reuse support.
In 2008, I wrote a post about classification, you can read it here. Meanwhile, the world has moved on, and I believe more modern classification methods exist.
Why classification ?
First of all classification is used to structure information and to support retrieval of the information at a later moment, either for reuse or for reference later in the product lifecycle. Related to reuse, companies can save significant money when parts are reused. It is not only the design time or sourcing time that is reduced. Additional benefits are lower risks for errors (fewer discoveries), reduced process and approval time (human overhead), reduced stock (if applicable), and more volume discount (if applicable) and reduced End-Of-Life handling.
Classification can also be used to control access to certain information (mainly document classification), or classification can be used to make sure certain processes are followed, e.g. export control, hazardous materials, budget approvals, etc. Although I will speak mainly about part classification in this post, classification can be used for any type of information in the PLM data model.
Depending on the industry you are working in, there are various classification standards for parts. When I worked in the German-speaking countries (the DACH-länder) the most discussed classification at that time was DIN4000 (Sachmerkmal-liste), a must have standard for many of the small and medium sized manufacturing companies. The DIN 4000 standard had a predefined part hierarchy and did not describe the necessary properties per class. I haven’t met a similar standard in other countries at that time.
Another very generic classification I have seen are the UNSPC standard, again a hierarchical classification supporting everything in the universe but no definition of attributes.
Other classification standards like ISO13399, RosettaNET, ISO15926 and IFC exist to support collaboration and/or the supply chain. When you want to exchange data with other disciplines or partners. The advantage of a standard definition (with attributes) is that you can exchange data with less human processing (saving labor costs and time – the benefit of a digital enterprise).
I will not go deeper into the various standards here as I am not the expert for all the standards. Every industry has its own classification standards, a hierarchical standard, and if more advanced the hierarchy is also supported by attributes related to each class. But let´s go into the data model part.
Classification and data model
The first lesson I learned when implementing PLM was that you should not build your classification hard-coded into the PLM, data model. When working with SmarTeam is was very easy to define part classes and attributes to inherit. Some customers had more than 300 classes represented in their data model just for parts. You can imagine that it looks nice in a demo. However when it comes to reality, a hard-coded classification becomes a pain in the model. (left image, one of the bad examples from the past)
1 – First of all, classification should be dynamic, easy to extend.
2 – The second problem however with a hard-coded classification was that once a part is defined for the first time the information object has a fixed class. Later changes need a lot of work (relinking of information / approval processes for the new information).
3 – Finally, the third point against a hard-coded classification is that it is likely that parts will be classified according to different classifications at the same time. The image bellow shows such a multiple classification.
So the best approach is to have a generic part definition in your data model and perhaps a few subtypes. Companies tend to differentiate still between hardware (mechanical / electrical) parts and software parts.
Next a part should be assigned at least to one class, and the assignment to this class would bring more attributes to the part. Most of the PLM systems that support classification have the ability to navigate through a class hierarchy and find similar parts.
When parts are relevant for ERP they might belong to a manufacturing parts class, which add particular attributes required for a smooth PLM – ERP link. Manufacturing part types can be used as templates for ERP to be completed.
Think part of the challenge moving forward is we’ve always handled these as parts under different methodologies, which requires specific data structures for each, etc. The next gen take on all this needs to be more malleable perhaps. So there are just parts. Be they service or make/buy or some combination – say a long lead functional standard part and they would acquire the properties, synchronizations, and behaviors accordingly. People have trouble picking the right bucket, and sometimes the buckets change. Let the infrastructure do the work. That would help the burden of multiple transitions, where CAD BOM to EBOM to MBOM to SBOM eventually ends up in a chain of confusion.
I fully agree with his statement and consider this as the future trend of modern PLM: Shared data that will be enriched by different usage through the lifecycle.
Why don’t we classify all data in PLM?
There are two challenges for classification in general.
- The first one is that the value of classification only becomes visible in the long-term, and I have seen several young companies that were only focusing on engineering. No metadata in the file properties, no part-centric data management structure and several years later they face the lack of visibility what has been done in the past. Only if one of the engineers remembers a similar situation, there is a chance of reuse.
- The second challenge is that through a merger or acquisition suddenly the company has to manage two classifications. If the data model was clean (no hard-coded subclasses) there is hope to merge the information together. Otherwise, it might become a painful activity to discover similarities.
SO THINK AHEAD EVEN IF YOU DO NOT SEE THE NEED NOW !
Modern search based applications
There are ways to improve classification and reuse by using search-based application which can index archives and try to find similarity in properties / attributes. Again if the engineers never filled the properties in the CAD model, there is little to nothing to recover as I experienced in a customer situation. My PLM US peer, Dick Bourke, wrote several articles about search-based applications and classification for engineering.com, which are interesting to read if you want to learn more: Useful Search Applications for Finding Engineering Data
So much to discuss on this topic, however I reached my 1000 words again
Classification brings benefits for reuse and discovery of information although benefits are long-term. Think long-term too when you define classifications. Keep the data model simple and add attributes groups to parts based on functional classifications. This enables a data-driven PLM implementation where the power is in the attributes not longer in the part number. In the future, search-based applications will offer a quick start to classify and structure data.
This is for the moment the last post about the difference between files and a data-oriented approach. This time I will focus on the need for open exchange standards and the relation to proprietary systems. In my first post, I explained that a data-centric approach can bring many business benefits and is pointing to background information for those who want to learn more in detail. In my second post, I gave the example of dealing with specifications.
It demonstrated that the real value for a data-centric approach comes at the moment there are changes of the information over time. For a specification that is right the first time and never changes there is less value to win with a data-centric approach. Moreover, aren’t we still dreaming that we do everything right the first time.
The specification example was based on dealing with text documents (sometimes called 1D information). The same benefits are valid for diagrams, schematics (2D information) and CAD models (3D information)
The challenge for a data-oriented approach is that information needs to be stored in data elements in a database, independent of an individual file format. For text, this might be easy to comprehend. Text elements are relative simple to understand. Still the OpenDocument standard for Office documents is in the background based on a lot of technical know-how and experience to make it widely acceptable. For 2D and 3D information this is less obvious as this is for the domain of the CAD vendors.
CAD vendors have various reasons not to store their information in a neutral format.
- First of all, and most important for their business, a neutral format would reduce the dependency on their products. Other vendors could work with these formats too, therefore reducing the potential market capture. You could say that in a certain manner the Autodesk 2D format for DXF (and even DWG) have become a neutral format for 2D data as many other vendors have applications that read and write back information in the DXF-data format. So far DXF is stored in a file but you could store DXF data also inside a database and make it available as elements.
- This brings us to the second reason why using neutral data formats are not that evident for CAD vendors. It reduces their flexibility to change the format and optimize it for maximal performance. Commercially the significant, immediate disadvantage of working in neutral formats is that it has not been designed for particular needs in an individual application and therefore any “intelligent” manipulations on the data are hard to achieve..
The same reasoning can be applied to 3D data, where different neutral formats exist (IGES, STEP, …. ). It is very difficult to identify a common 3D standard without losing many benefits that an individual 3D CAD format brings currently. For example, CATIA is handling 3D CAD data in a complete different way as Creo does, and again handled different compared to NX, SolidWorks, Solid Edge and Inventor. Even some of them might use the same CAD kernel.
However, it is not only about the geometry anymore; the shapes represent virtual objects that have metadata describing the objects. In addition other related information exists, not necessarily coming from the design world, like tasks (planning), parts (physical), suppliers, resources and more
PLM, ERP, systems and single source of truth
This brings us in the world of data management, in my world mainly PLM systems and ERP systems. An ERP system is already a data-centric application, the BOM is already available as metadata as well as all the scheduling and interaction with resources, suppliers and financial transactions. Still ERP systems store a lot of related documents and drawings, containing content that does not match their data model.
PLM systems have gradually becoming more and more data centric as the origin was around engineering data, mostly stored in files. In a data-centric approach, there is the challenge to exchange data between a PLM system and an ERP system. Usually there is a need to share information between two systems, mainly the items. Different definitions of an item on the PLM and ERP side make it hard to exchange information from one system to the other. It is for that reason why there are many discussions around PLM and ERP integration and the BOM.
In the modern data-centric approach however we should think less and less in systems and more and more in business processes performed on actual data elements. This requires a company-wide, actually an enterprise-wide or industry-wide data definition of all information that is relevant for the business processes. This leads into Master Data Management, the new required skill for enterprise solution architects
The data-centric approach creates the impression that you can achieve a single source of the truth as all objects are stored uniquely in a database. SAP solves the problem by stating everything fits in their single database. To my opinion this is more a black hole approach: Everything gets inside, but even light cannot escape. Usability and reuse of information that was stored with the intention not to be found is the big challenge here.
Other PLM and ERP vendors have different approaches. Either they choose for a service bus architecture where applications in the background link and synchronize common data elements from each application. Therefore, there is some redundancy, however everything is connected. More and more PLM vendors focus on building a platform of connected data elements, where on top applications will run, like the 3DExperience platform from Dassault Systèmes.
As users we are more and more used to platforms as Google, Apple provide these platforms already in the cloud for common use on our smartphones. The large amount of apps run on shared data elements (contacts, locations …) and store additional proprietary data.
Platforms, Networks and standards
And here we enter an interesting area of discussion. I think it is a given that a single database concept is a utopia. Therefore, it will be all about how systems and platforms communicate with each other to provide in the end the right information to the user. The systems and platforms need to be data-centric as we learned from the discussion around the document (file centric) or data-centric approach.
In this domain, there are several companies already active for years. Datamation from Dr. Kais Al-Timimi in the UK is such a company. Kais is a veteran in the PLM and data modeling industry, and they provide a platform for data-centric collaboration. This quote from one of his presentations, illustrates we share the same vision:
“……. the root cause of all interoperability and data challenges is the need to transform data between systems using different, and often incompatible, data models.
It is fundamentally different from the current Application Centric Approach, in that data is SHARED, and therefore, ‘NOT OWNED’ by the applications that create it.
This means in a Data Centric Approach data can deliver MORE VALUE, as it is readily sharable and reusable by multiple applications. In addition, it removes the overhead of having to build and maintain non-value-added processes, e.g. to move data between applications.”
Another company in the same domain is Eurostep, who are also focusing on business collaboration between in various industries. Eurostep has been working with various industry standards, like AP203/214, PLCS and AP233. Eurostep has developed their Share-A-space platform to enable a data-centric collaboration.
This type of data collaboration is crucial for all industries. Where the aerospace and automotive industry are probably the most mature on this topic, the process industry and construction industry are currently also focusing on discovering data standards and collaboration models (ISO 15926 / BIM). It will be probably the innovators in these industries that clear the path for others. For sure it will not come from the software vendors as I discussed before.
If you reach this line, it means the topic has been interesting in depth for you. In the past three post starting from the future trend, an example and the data modeling background, I have tried to describe what is happening in a simplified manner.
If you really want to dive into the PLM for the future, I recommend you visit the upcoming PDT 2014 conference in Paris on October 14 and 15. Here experts from different industries will present and discuss the future PLM platform and its benefits. I hope to meet you there.
Some more to read: