MIDIH RA for Smart Supply Chain 3 MIDIH Modular and Functional Architecture Considering the RAMI4.0, the IIC reference architecture model (IIRA) and starting on the premise that the MIDIH Reference Architecture will include a “platform” or “middleware” Swafford et al. Supply chain management SME all-in-one information Preventive maintenance Asset and equipment management Maintenance service management 2A01 Digitalization of process information and know-how on manufacturing ... Industrial Value Chain Reference Architecture Author: Yasuyuki Nishioka In addition to the primary storage layer in Data Lake Store, we use a broad array of building blocks in Azure, with the key components being: Figure 1 highlights the architecture that surrounds Data Lake Store for our end-to end-solution. Creating predictive and prescriptive models. The supply chain engineering team at Microsoft provides solutions for core supply-chain functions related to hardware and devices like Microsoft Surface, Xbox, and HoloLens. Building on the co-specialization perspective, we evaluate the performance implications of product modularity and supply chain agility. Data Lake Store includes encryption and auditing, in addition to role- and POSIX-based controls at the folder level. Our supply chain engineering team at Microsoft used to store and process data in disparate systems, which made data sharing and forecasting harder. With hardware, you have dedicated servers for environments like development, testing, and production. A reference architecture in the field of software architecture provides a template solution for an architecture for a domain. Data Lake Store has a file system like the one on your personal computer. The supply chain reference model encompasses a pyramid with four levels: 1. The Gartner Supply Chain Architecture Life Cycle (SCALe) is the process of managing the entire life cycle of each capability within your supply chain. Designing and Managing the Supply Chain: Concepts, Strategies, and Case Studies. ... Reference architectures for manufacturing and supply chains such as ISA-95 and SCOR. We empirically test the hypothesized relationships using data collected from 103 manufacturing firms. While a data lake doesn’t solve all problems, and may create a few new ones, it allows more immediate focus on value-added activities and innovation with data. ScienceDirect ® is a registered trademark of Elsevier B.V. ScienceDirect ® is a registered trademark of Elsevier B.V. How supply chain architecture and product architecture impact firm performance: An empirical examination. Supply chain agility is a unique process configuration that can support organizational competitiveness. Data assets are categorized as raw, gold, or cooking: Figure 3 shows the process we followed to move from a data-warehouse-centric platform to our modern platform. (2006) define supply chain agility as the ability of an organization to adapt and react to marketplace changes or to seize/exploit market opportunities with speed and quickness. Part 1: Reference Architecture Smart Manufacturing Unit (SMU) Smart Manufacturing is a system of systems that faces ... demand/supply chain and the flow of engineering information and knowledge have a point of intersection. Figure 5. Agile practices improve delivery performance and reduce costs, two outcomes often portrayed as competing objectives. Topics include using Git, GitLab, and the Docker Hub to feed the supply chain. By continuing you agree to the use of cookies. Or, the engineering teams can manage it. Provided simpler support for large-scale encryption at rest and in transit. with other data. Both the product and supply chain architectural decisions can impact performance, individually and in conjunction with each other. "Supply Chain Architecture" is highly effective as a guide for approaching Supply Chain network development because the depth of the content is matched by the book's very orderly approach in showing the Supply Chain professional how to proceed. Examples of these functions include sourcing of materials, planning, manufacturing, delivering products to consumers, and managing the customer care process. In the end-to-end supply chain process, the right insights make it easier to identify trends and risks that help you ship on time, provide a quality product, save costs, and optimize inventory. E2open’s Independent Review of Gartner’s Technology Reference Model for Stage 5 Maturity in Supply Chain Planning Shows E2open Multi-Enterprise Solution Architecture Meets Benchmark for Future-Proof Supply Chain. They need data about what’s failing and why. The paper uses three perspectives on enterprise architecture (EA) in the supply chain: The correlation view, the remote view and the institutional view. Supply Chain Architecture & Strategic Planning It is estimated that only 4 to 14 percent of the value that is sold to the end customer is actually generated within the selling enterprise. But in preparation for Industry 5.0, in which humans will work side by side with robots to deliver value-added tasks, enabling supply chain models must also flex and evolve. This thesis aims to 1) clarify the concept of control tower within the supply chain sector by providing a standardized definition, 2) provide a generalizable reference architecture for the supply chain control tower to assist transition toward it, 3) design a prototype … This concept goes beyond intra-organizational boundaries to achieve a greater value of the entire supply chain network. from early of 1900s, and was created to reengineer. The data moves through the links in the chain, incrementally acquiring value. Blockchain, Enterpris e architecture, Reference mode l, Supply chain, Use case. For example, we don’t have to worry about whether our infrastructure can accommodate ever-increasing amounts of data that we need to store and process. The Secure Supply Chain can be broken into three stages: This move to Data Lake Store has: Someday the industry may realize the dream of data federation, but today there’s big value in centralizing data and then connecting that data to our supply chain processes. Allowed us to quickly onboard new data assets—what used to take weeks now takes days. The decision to implement our data lake in Data Lake Store meant we could realize the benefits of three of these principles, right out of the box. We have out-of-the-box support for enterprise security and compliance, including Azure Active Directory authentication, and folder-level authorization via role-based and POSIX-style access control lists (ACLs). ... it is a great source of reference in the research arena. Results show that supply chain agility and product modularity directly enhance responsiveness and enable organizations to reduce cost. Enabled us to say “yes” and take on more business requests, by giving us flexibility, scale, and speed. While a common result of organic growth over time, this approach can make it difficult to connect the pieces and optimize the whole. To move data from one environment to another, point your source to the desired location. All the tools listed and demonstrated within this reference architecture can be replaced with alternatives. First, the reference architecture provides a hybrid solution of centralised and decentralised supply chain systems that combines advantages of the IoT and cloud computing. As illustrated in Figure 2, a connected retail L0 Architecture comprises proprietary systems such as those required for merchandising, order management, supply chain, and distribution. Sunil Chopra and Peter Meindel. Day-to-day operations involve gathering, storing, processing, and visualizing data by: From start to finish, our team process works as follows: To achieve our business goals, we needed a modern architecture that could serve as a foundation for digital transformation in the supply chain. That’s what the new Digital Capabilities Model for Supply networks is all about. A great example of this pattern is the refrigerated transportation of perishable goods like food or pharmaceuticals where certain compliance rules must be met throughout the duration of the transportation process. A broader level definition is offered by Braunscheidel and Suresh (2009). It’s a new supply chain framework that incorporates emerging drivers of success. Our approach for moving to a data lake. Modeling the Supply Chain. A common blockchain pattern is IoT-enabled monitoring of an asset as it moves along a multi-party supply chain. SUPPLY CHAIN ARCHITECTURES IN AN E-ENVIRONMENT Dragana Rejman Petrovic, * Igor Milanovic, Zoran Kalinic The concept of supply chain management (SCM) has occupied serious research a! Duxbury Thomson Learning, 2001. With a data lake, your folder structure can be your environment, with roots for testing, development, and production. A supply chain is the network of people, organizations, resources, processes, and technology that are needed to create, distribute, and sell a product. At last, we combine the supply chain management and the latest object oriented technology, then propose an architecture of supply chain management systems. To co-locate data in a data lake effectively, determine how you’ll design and organize it. The arrow from bottom to top demonstrates increasing levels of data curation. While there are obvious business benefits to adopting a big data platform, this was largely about technology modernization in the short-term with a focus on preserving business continuity. Jeremy F. Shapiro. To aggregate data and connect our processes, we built a centralized, big data architecture on Azure Data Lake. These supply chain activities are highly interconnected and interdependent, yet we’ve often operated in silos—with data in disparate systems and supply chain teams making isolated decisions. The folder structure in Data Lake Store reflects the levels of governance and ownership. To do so, the designed system includes a local instantiation of the workflow controller, which allows for disconnections from the Internet, e.g. Careful design choices in the folder structure will make governance much easier. The Supply Chain Operations Reference (SCOR) model is unique in that it links business processes, performance metrics, practices, and people skills into a unified structure. 1. To aggregate data and connect our processes, we built a centralized, big data architecture on Azure Data Lake. Definition of the 26 core supply chain process Bringing digital transformation to the supply chain with Azure IoT Suite. Supply Chain Management Systems: Architecture, Design and Vision Vikas Misra University of Petroleum and Energy Studies, Dehradun, India M.I.Khan Integral University, Lucknow U.K.Singh K.N.I.T. Supply chain industry reference architecture. the supply chain management software architecture using the ALMA method. Manufacturers, for example, need real-time—or earlier—information when defects occur. Create accurate demand forecasting for hardware and devices for consumers, online stores, and frequent orders. Treat data as a shared asset. How supply chain architecture and product architecture influence organizational competitiveness. These systems are backed by underlying databases that include multiple services hosted for various business domains. For example, you wouldn’t store all your documents in the C: root directory. Sultanpur A supply chain is a network of suppliers, factories, warehouses, distribution centers and retailers, This reference architecture describes the components that make up a Secure Supply Chain. This, in turn, makes it even more challenging to apply advanced analytics and machine learning for deeper insights. Connected Retail Reference Architecture (L1) 14 15. While we still move small subsets of data to a database or reporting tool, we can meet many of our use cases by simply layering our compute engine in Spark over Data Lake Store. It is hierarchical in nature, interactive and interlinked. Ensure security and access controls. The data in high-level folder paths can be user-owned, where individuals and teams can set their own policies locally. It’s similar with a data lake—everything is a file, with other options that can be tailored to a given requirement. The supply chain ends with actionable, valuable business insights— such as ideas for new product, service, or process innovations, marketing campaigns, © 2018 Elsevier Ltd. All rights reserved. architecture of supply chain management. Figure 3. While, product modularity constitutes a product configuration related to sourcing and assembling of products, supply chain agility is a supply chain configuration related to velocity (sensing, comprehending, and responding) and visibility (supplier network, internal operations, and external environment). Often, you need data in your test environment that’s similar in size and quality to production data. Supply chain track and trace A common blockchain pattern is IoT-enabled monitoring of an asset as it moves along a multi-party supply chain. We elaborate on the key contributions of this study for both research and practice, discuss limitations, and also offer various avenues for further research. Google hardware, software, and services are built with security as a primary design concern. Supply chain industry reference architecture Code patterns Code patterns Resources Product information From source to consumer, manage your supply chain. Eliminate data copies and movement. Applying a computing engine to process the data by using Spark. Enabled application-independent compute engines to be provisioned over a shared data foundation. The platform team defines the architecture, designs solutions, performs data engineering, and automates and supports the solution from code to consumption. Rather than moving data between environments, you’re just reading the data using a different path. It also provides a common vocabulary with which to discuss implementations, often with the aim to stress commonality. With this layering, we enable SQL-like experiences with Hive or any other supported capabilities in Spark, like machine learning, all with zero data movement. This document is for informational purposes only. If you’re planning to implement a similar solution for your supply chain data, here are a few points to consider: Figure 2 shows an example of our approach. Our business partners build and maintain most of the presentation layer, including Power BI dashboards and SQL Server Reporting Services reports. Use data to identify why a device failed, predict manufacturing yield rates (the number of manufactured products that pass inspection the first time), and predict or even prevent future failures. Copyright © 2020 Elsevier B.V. or its licensors or contributors. Further detail is industry and organization specific (level 4 … Important to explore complementariness between agile practices and modular product architecture. ention in recent years. Our roadmap includes using what we’ve already done as a foundation and layering other capabilities including: Driving Microsoft's transformation with AI, Unleash the full power of data with a modern data platform. Introduction. For example, business partners might own everything that’s stored in a particular location and have authority over it. In a blog post from 2016, Josh Klahr—VP of Product Management at AtScale—proposed six architectural principles that influenced our solution. Supply-chain operations reference (SCOR) model is a process reference model developed and endorsed by the Supply Chain Council as the cross-industry, standard diagnostic tool for supply chain management. Our engineering team also builds denormalized information assets including Kimball-style dimension and fact tables housed in Azure SQL Data Warehouse and OLAP cubes. © 2020 Microsoft Corporation. An early step in this transformation was to bring this disparate supply chain data into one location—a data lake—rather than managing multiple data warehouses or manually co-locating data on an ad hoc basis. In this part, the UML notation will be introduced. Now, we’ve improved data quality and visibility into the end-to-end supply chain, and we can use advanced analytics, predictive analytics, and machine learning for deep insights and effective, data-driven decision-making across teams. Journal of Purchasing and Supply Management, https://doi.org/10.1016/j.pursup.2018.02.003. The blockchain data manager captures block and transaction data from configured transaction nodes, decodes events and properties and then sends the data to configured destinations. SCOR® provides standards down to the level where process descriptions are applicable across a range of industries. Data in another location might be managed by the engineering team and could have source-control mechanisms in place. The server receives forecasts for direct material procurement from the customers detailing the orders that the customers desire. Learn more about the steps we take to secure our hardware supply chain. We collaborate with our business partners to determine what data is needed to move the business forward. In each activity, there are corresponding hierarchical Specifically, it’s a platform that allows you to gather, store, and process data of all sizes and types, from any data source, and that enables you to access it seamlessly to gain valuable insights. Data Lake Store, the Microsoft hyperscale repository for big data analytic workloads, is essentially Hadoop for the cloud made simple. Data Lake Store can store and enable analysis of all our data in a single layer. Establishes the competitive objectives, the key supply chain process type: plan, source, make, and deliver. David Simchi Levi, Philip kaminsky, and Edith Simchi Levi. Furthermore, supply chain agility partially mediates the relationship between product modularity and both responsiveness and cost reduction. 2. Then, we will introduce object oriented analysis and design. The names of actual companies and products mentioned herein may be the trademarks of their respective owners. Supply Chain Management: Strategy, Planning, and Operation, Prentice Hall of India, 2002. The Open Group IT4IT Reference Architecture is a standard reference architecture and value chain-based operating model for managing the business of IT. The digital transformation journey is one that Microsoft has already begun, as discussed in Bringing digital transformation to the supply chain with Azure IoT Suite. The Best Gets Better Although SQL Server continues to play an important role in the presentation of data, it’s just no longer a central storage component. A supply chain network where customers, suppliers, logistics providers, carriers, and financial institutions are all connected to a centralized supply chain server. Conceptualization of supply chain agility can be used by organizations to gauge areas of strength and areas that need improvement. (over 6 Billions of transactions) 15 Use Case I – High volume message routing 16. In order to enhance performance, manufacturing firms are building various capabilities and utilizing supply chain networks that are geographically dispersed around the globe. Find the best prices for parts from suppliers and predict supplier prices at a component level for future buying optimization. The power of data—data that shows patterns and predicts what’s ahead—helps to fuel digital transformation in the Microsoft supply chain. Figure 4: Supply Chain Operations Reference (SCOR) model from Supply Chain Council Apart from SCOR model, the Supply Chain Council has also published Design Chain Operations Reference (DCOR) model and Customer Chain Operations Reference (CCOR) model extending into other areas of business operations not in the scope of the SCOR model. This study examines how decisions related to supply chain architecture and product architecture influence organizational competitiveness. The history of supply chain ma nagement started. It includes all the components that contribute to the major supply chain activities of plan, make, and deliver. The Supply chain industry reference architecture is a high-level view of a best-in-class supply chain landscape. It uses a value chain approach to create a model of the functions that IT performs to help organizations … When this happens, you must physically move it from production to testing and back. To tackle these challenges and bring our data together, we moved from a traditional relational database-centric solution to a big data platform with Azure Data Lake Store as its foundation. The co-location and scalability of Data Lake Store enables us to use the lake for a wide range of use cases and diverse target audiences. MICROSOFT MAKES NO WARRANTIES, EXPRESS OR IMPLIED, IN THIS SUMMARY. Gathering and storing the data in Data Lake Store. ๏ Ultra fast Message routing with low latency. Our supply chain engineering team at Microsoft used to store and process data in disparate systems, which made data sharing and forecasting harder. The SCOR model describes the business activities associated with satisfying a customer's demand, which include plan, source, make, deliver, return and enable. One building block of digital transformation is a modern data and analytics platform. Even so, we defined some key scenarios that would help us prioritize what to go after on the new platform: We help the supply chain by providing intelligence and data to make our planning and daily operations run more smoothly—and to optimize costs. A modern data supply chain begins when data is created, imported, or combined . We use cookies to help provide and enhance our service and tailor content and ads. We’ve also built a robust data quality engine by using all Azure components, which serves as the centerpiece of our live-site process. Expanded conceptualization of supply chain agility to include comprehending as an additional dimension. Supply chain operations reference Model ... and the implementation of the architecture (level 3 processes). Connected Retail Reference Architecture (L0) 13 14. A few of the challenges we’ve faced, but have overcome, include: Some of the lessons we’ve learned thus far include: So far, we’ve seen the following benefits: We’re still in the early stages of digitally transforming our supply chain, but we’re already seeing the benefit of having centralized data, a more flexible data processing model that scales as needed, and connected processes. We partner with the data science team who uses the platform to assist the business with analysis, and to gain deep insights through econometric modeling and machine learning.