For the last decade, PLM and information technology have become the foundation for building a competitive edge. PLM expanded and became critical to meeting customer needs and expectations that require increased speed to market, shorter time-to-profitability, and decreased cost of goods sold. Digital transformation is a critical factor in this journey and, as enterprises are moving into a modern digitally connected world, the ability to optimize product development, manufacturing, and services is what drives business value and success today. It has never been more important for manufacturers to make sure they have the right IT infrastructure in place because it can be difficult if not impossible to scale your operations without an effective IT strategy in place. What role the modern PLM system will play in this transformation is a critical element of future enterprise IT development.
In my article today, I’d like to continue the discussion about digital enterprise, will talk about what role product lifecycle management (PLM) will play in the digital transformation and how semantic technologies will transformation enterprise systems. It is the next article in my series of articles about the digital enterprise. If you missed my previous article, please check it here – Semantic Foundation of Digital Enterprise.
Rethinking Technology Foundation Of Digital Transformation
The future will belong to the companies that will be able to transform themselves to support modern digital business principles to optimize business value using new data management, organize critical product data structure, build digital twins of their product, organize holistic configuration management process and eventually focus on total customer satisfaction, optimization of supply chains and to use product-related information to manage their businesses. Such a bright future is impossible without rethinking the foundation – IT technologies and product lifecycle management, which is a core behind new product innovation. PLM solutions that are capable to help customers to achieve their goals will be in high demand. What will happen with the existing PLM software is another big question giving the number of resources and investment manufacturing companies put into the organization of these PLM tools and business processes around these tools.
Industrial enterprises need to operate with a high level of agility and intelligence. Their ability to achieve it depends largely on the enterprise IT foundation, which will allow them to continually upgrade both digital business capabilities and the technologies underneath these business functions. For companies whose enterprise IT technologies lock them in the old pre-digital business processes and tech, competing against pure digital companies will create a big problem. Therefore industrial companies in all industries are racing to digitally transform their business models and infrastructure.
Unfortunately for many industrial companies, their foundation is relying on 20-30 years old technologies stack. When it comes to product data management, manufacturing resource planning, and supply chain, we can see many legacy PDM/PLM/ERP systems with siloed approaches, old document-driven architecture, and legacy databases.
The biggest challenge is to transform such environments without disrupting existing operations, gradually rebuilding and replacing applications, and leverage enormous amounts of valuable data collected in existing databases, documents, and legacy data sources. Existing supply chain management system, PLM system, document management, requirements management needs to be aggregated and gradually replaced with modern business systems.
The semantic foundation of the transformation is to have an information layer that can be used to semantically describe the meaning of the data, build required relationships and establish connections between data silos to support seamless business processes.
PLM Architecture Approach – Old vs New
To bring a semantic foundation to the information technology stack requires breaking a traditional PLM architecture approach. This transformation won’t happen overnight – it is a gradual approach, the transformation that will be happening by introducing new services and replacing old elements, applications, and databases.
Below, I bring five principles of architecture transformation.
- From product-oriented approach (applications) to integrated services (SaaS).
- From SOA and tightly coupled applications to independent services
- From heavy service integrated “bus” to lightweight RESTful connections
- From centralized IT approach to agile DevOps
- From specialized hardware configurations to commodity computing services
The Role And Application Of Semantic Foundation
Let’s get back to the semantic foundation of the information technological stack. In my view, it will play a key role in setting up connectivity and interoperability between services. The biggest challenge in existing applications is establishing interoperability and data exchange. The new architecture approach will be relying on the usage of online services with the ability to provide instant access to the data. These data services will rely on a semantic data layer to support data understanding, transformation, and usage in different applications and data services.
An interesting question that is always asked by PLM architects about semantic technology applications is how and who will create ontologies to describe the data. Here is my take – the power of semantic stack is not in the definition of a specific universal or standard ontology. It is actually the opposite, the power of the semantic stack is to provide standards to describe the data. So, I’d not expect a single PLM ontology, but I’d expect new PLM services to be enabled to support RDF/OWL and to make online services capable to manipulate the data using multiple data structures with the semantics described using RDF/OWL. Similar to how it happened to earlier PLM applications and technologies, the OOTB approach never really worked. Flexibility is the key and after the earlier attempts to use universal ontologies, the next step will be to bring more flexibility and allowance to companies to use RDF/OWL as an enabler in data description.
Here is one practical example – components reuse and parameters classification of items consumed from multiple services. A catalog item service can use specific enterprise ontology to transform a set of parameters from one vendor standard to another. Such an easy data transformation can be enabled by applying elements of RDF/OWL modeling. Such service can become a foundation of online component libraries using in online product data services (SaaS) in bill of materials management, service operations, maintenance applications and many others.
The new IT foundation and data architecture are required to build a digital enterprise. Old PLM and enterprise IT relied on siloed applications and used heavy integrations to map the data and synchronize the information between silos. The new PLM and Information IT approach will be relying on independent services, DevOps, and will use a semantic data layer to describe the information to be consumed by multiple services. The ontologies and semantic data layer will be built over a period of time-evolving together with technologies to manage the product lifecycle, organize digital thread, and bring new flexible service-oriented PLM software to the industry. Just my thoughts…
Disclaimer: I’m co-founder and CEO of OpenBOM developing a digital network-based platform that manages product data and connects manufacturers, construction companies, and their supply chain networks. My opinion can be unintentionally biased.
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