The company is market leader for polishing products to the semiconductor industry and have multiple production plants around the globe. As market requirements keep on increasing and time to market is essential, analytics and supply chain have been identified as the key enablers to facility their strategic and business objectives.
To fulfill their strategic and business objectives the company want to transform their current way of working towards an integrated horizontal and vertical value chain.
Although the company has excellent data scientists, the current data management and analytics methods & technics are not sufficient to support the strategic and business objectives.
The company wants to collect more manufacturing data globally and introduce broader range of analytics capabilities. It means they want to create a dynamic data lake environment that is able to collect real-time data from the different plants and offers insight to different users from a single version of the truth philosophy . An additional requirement is that the lifecycle cost of such an environment should be less than 30 % of the cost of typical solutions in the market.
This use case will show how using a holistic based modelling solution approach gives insight in different design options, including and the impact on process, applications, infrastructure and related cost.
The following business objectives are in scope:
• Right First Time
• End to End insight on production process details
• End to end insight on product quality
• Reduce root cause from several months to days
• Improve supply chain
• Reduce Waste
• Fast Return on Investment
Continuous delivery of insights for the millions of experts to make smarter, better and faster decisions
that can be controlled and managed during the full transformation lifecycle.
For the manufacturing IT, applications from GE Intelligent Platform and HMI, and Rockwell PLC are used. The different design options and costs need to be evaluated, but as there is no enterprise architecture strategy and tools, it is not possible to have fact based inside. This lead to different opinions and assumptions from the several expertise with no business feasibility for management decisions.
The current manufacturing IT and Business IT are not integrated, and there is no enterprise architecture approach in place. Manufacturing data is captured by historians isolated on plant level, while the manufacturing process information is stored in several other databases
Applications and infrastructure are managed on available knowledge of the expert which lead to long effort and time to make any change.
The pain points can be summarized as:
• Customer complaints because of product quality variation
• No sufficient data collection and data preparation possibility lead to several months on root cause analysis of a problem
• High cost and inefficiency of data scientists
• No single version of the truth’
• Cannot innovate fast enough
• No possibility to capture lessons learned
• Culture of ‘hero’s
We used the unique Smart Industrial Transformation approach and Models4Insight holistic modelling platform to create and manage digital representations of the users, process, applications and physical assets, taking into account the actual current situation and the ‘To-Be’ scenarios.
The approach uses models to describe the different constituents ranging from business goals down to the shopfloor infrastructure and physical assets
For this situation different types of possible applications to collect big data from the plants as well as to create a dynamic data lake has been simulated and impacted analysis was performed using the holistic digital representations. In parallel several analytics tools were evaluated, creating live demo’s. Applications involved in the evaluation ranges from tier 1 to tier 3 providers.
In particular, 6 different solution alternatives have been modeled and compared with regards to cost, user friendliness, and other criteria. The design views have been made for the central IT. In conversations with the different plants, we have turned these views focusing on a single pland and displaying the most significant choices in a single view for that plant to discuss the impact on their current IT landscape and to illustrate the differences between the two alternatives.
Figure below illustrates this comparison for two design alternatives for a single plant.
In the Smart Industrial Transformation Approach models are used in a specific way:
• Scenarios are modelled from different point of views like e.g. for a manufacturing process: the physical object view, the machine view, the operator view and the process engineer view. These four views together describe the actual process best.
• Scenarios are modelled in the most detailed way and semi-automatically derive higher level views, thus views with lesser detail. These different views with varying level of detail are required for different groups of people. A manager just wants to see the high level picture, while a process engineer wants to see all details. By deriving the higher level views we ensure that the different levels of details are consistent with each other.
Stakeholders are able to visualize the ‘As-Is’ and the ‘To-Be’ situation, and do scenario play and impact analysis to manage process and application migration.
Our assessment framework is uniquely tailored for Industry 4.0, Industrial Internet of Things, and Digital transformation. It is supported by a Smart Industrial Transformation approach, based on holistic modelling.
By using our unique Smart Industrial Transformation deployment framework we make sure that your deployment will be better, smarter and faster.
It is the only solution that is able to integrate and digitize the different dimensions of, Users, Suppliers and Customers, Processes, Applications, Physical assets, Infrastructures and Data, needed for best in class transformation deployments.
The basis is the ability to create digitized templates, which brings your templates alive and enables you to constantly control, manage the uncertainty and have maximal agility during your deployment journey.
The digitized transformation template is typically used to manage the deployment of:
Global (MES) applications;
IT-OT architecture in general as well as more specifically RAMI 4.0 (Reference Architecture Model Industrie 4.0);
Digitized System Architecture Transformation – Architecture and application deployment of OEM machines;
Our Smart Industrial Transformation based roadmap framework is a holistic modelled framework uniquely tailored for Industry 4.0, Industrial Internet of Things and Digital transformation.
It is the only solution that brings alive your roadmap by digitizing it. With this you are in constant control, able to manage the uncertainty and have maximal agility during the journey.
The roadmap framework is typically used to get insight and input:
• To align Users, Suppliers and Customers, Processes, Applications, Physical assets, Infrastructures and Data dimensions;
• To understand the impact and execution of your roadmap items;
• for insight on impacts of roadmap items;
• for your IT-OT (Information Technology – Operational Technology) Architecture;
• for roadmap agility;
By using our unique Smart Industrial Transformation architecture framework we make sure that your architecture will be at the life cycle management level to meet Industry 4.0. IIoT (Industrial Internet of Things) and Digital transformation requirements
It is the only solution that is able to integrate and digitize the different dimensions of, Users, Suppliers and Customers, Processes, Applications, Physical assets, Infrastructures and Data, needed for Industry 4.0 architecture. This brings your architecture alive, enabling you to constantly control, manage the uncertainty and have maximal agility during your transformation journey.
The architecture framework is typically used to design and manage:
IT-OT architecture in general, incl. impact analysis;
Specific RAMI 4.0 (Reference Architecture Model Industrie 4.0);
Digitized System Architecture Transformation – Architecture and application redesign of OEM machines;
Smart Manufacturing (data) architecture with advanced analytics capabilities;
We offer modelling services to be able to create digital formal models (digital twins) for Industry 4.0, II0T and Digital transformation. Those models are digital representations covering processes, applications, infrastructures, physical assets and contextualized data.
The modelling is based on de ArchiMate architecture language using our Models4Insight™, IP based Modelling & Insight solution platform, It enables you to design, create, enhance, manage, store and retrieve digitized integrated models giving a formal digital representation making you in control of your Industry 4.0, IIoT and Digital Transformation journey. It is offered as a free public version or private subscription based service.
Our mission is crisp and clear: Continuous delivery of insight for the millions of experts to make smarter, better and faster decisions that can be controlled and managed during the full lifecycle. Read more