1 April 2007
Linking all supply chains
Spreadsheet management out; common data repository in
By Tomas Montin
Right before the turn of the century, specialty oil maker Nynas faced serious challenges arising from fragmented data sources within its supply chain.
Separate, individualized and non-standardized planning bases meant poor visibility into the production plan across the enterprise, and weak links between corporate planning and refinery planning resulted in sub-optimal refinery production schedules.
One of the main problems came when users started planning. It seemed different parts of the supply chain would come from different data sources. Quite often, there was significant deviation between these data sources, which affected the quality of planning.
The use of spreadsheet models, where each spreadsheet covered just a small part of the supply chain, made the planning process fragmented, resulting in a lack of oversight and sub-optimized plans. Also, generation of the site material balance was tedious work; the only way to extract the data from different systems was through a manual process. In addition to being labor-intensive, this manual process often resulted in lost data and data discrepancies.
In an effort to identify how the company could improve its supply chain, Nynas retained a consulting firm to perform a study. The study focused on planning and scheduling/data integration for the optimization of the refineries.
The study recommended a streamlining of the manual processes used for data collection to allow more time to focus on data analysis. The study also recommended Nynas link the individual refineries more closely to the corporate planning process.
The solution was to install a common data repository to aggregate, consolidate, and reconcile data from disparate sources; integrate operational, business, and real-time market information; and enable desktop access to consistent 'master data' that covers every aspect of plant operations. As a vendor-independent platform, the data repository would also make use of the legacy automation and IT infrastructure.
The system consists of three main components:
Repository: Database and plant data model. The repository is a fully implemented plant data model that encompasses virtually all objects, activities, and processes within the plant, and acts as a warehouse for plant data. Repository consolidates information from multiple systems, providing single-window access to all plant information. It also contains a dynamic calculation engine that can use local and remote information to compute complex indicators automatically or on demand.
Relayer: Data transport and translation. Relayer is a messaging component that handles this message routing while also providing comprehensive translation services. Relayer "listeners" can either respond to incoming messages or raise their own events based on user defined criteria and calculations. Relayer's standard functionality includes automatic buffering to ensure system and network interruptions do not lead to lost messages or cause delays to host system operation.
RISNet: Thin client interface. RISNet is a complete environment for the creation and deployment of Web-based user interfaces to repository, allowing thin-client access to integrated plant and business data wherever personnel happen to be. RISNet allows location-independent visibility of plant operations without additional IT infra- structure.
As deployed at Nynas, the data repository contains a business model of the company structured in a hierarchical tree, with the different products in the supply chain handled in a similar way and consistently identified in the commodity explorer. In one example, the bitumen quality 160/220 would have more than 10 different names in inventory systems, scheduling systems, LP models, etc.; but within the data repository, it has a single identity.
The data repository allowed Nynas to establish a highly integrated supply chain. The generation of a weekly refinery schedule, depot replenishment schedule, and shipping schedule can act as a data conveyor or a data repository.
The current planning cycle runs as follows:
The demand management system estimates sales in different regions, per commercial quality. Commercial qualities group into base (tank) qualities and split the demand between different depots.
The demand goes into the depot planning system together with inventory information supplied from tank radar meters. The system will plan transports to depots and wholesale customers, taking into account product availability at the refinery, tank space at the depot, and ship sizes.
The shipping department uses a module to plan each individual ship route. Requested liftings and ships connect and the estimated time of arrival and estimated time of departure change accordingly.
The refinery planner loads updated refinery inventories and the lifting schedule into the scheduling tool. They can then store the refinery schedule, which generates a web-based production plan, which can then go out to the operators.
The corporate planning model can predict future inventories for depots and refineries. Inventory projections compare against aggregated monthly demand data.
Information made easier
The new system allows Nynas to retrieve data from different sources and correlate it in a common model, generating valuable information that would have been impossible or prohibitively labor-intensive to obtain from the previous system.
The system has links to the process information system at the refinery, allowing a comparison of planned versus actual production and performance. In the online business model, it stores the yield and product structure per process unit information, making it possible to identify the product that has undergone measurement by a certain flow meter at a particular time.†
The system stores the specification limits for all units and all modes of operation. The information transfers into the plant information system as well as into the distributed control system. This makes it possible to trend lab data and inferred data against limits, and to quickly and easily calculate deviation from targets.
The new system is also the primary tool in generating monthly site material reports at the refineries. The report generates from inventory changes as well as imports and† exports from the refinery.
The new system ends up being the interface between the production systems and the ERP system. Therefore, information about loaded quantities on trucks and ships transfer to the ERP system.
The application updates with a fully Web-enabled presentation system, RISNet. In addition to increasing the accessibility of the system, Web access has also simplified maintenance.
As use of the new system becomes more extensive within the operations, the reliability of the system becomes critical. Nynas continues to work with its integrator, Matrikon, to develop a fault-tolerant IT architecture, which also allows system maintenance to go on during operation without interrupting the workflow or planning cycle.
Although difficult to quantify in monetary terms, the project allowed for higher accuracy of planning information. It reduced the risk of stock outs at bitumen depots, while tighter integration of depot and refinery planning meant fewer mode changes and higher batch yields. The ability to easily compare planned versus actual production and performance has given a boost to Nynas' ongoing performance improvement efforts.
ABOUT THE AUTHOR
Tomas Montin (Tomas.firstname.lastname@example.org) is the planning manager for logistics at Nynas Refining.
Supply chain management: Back to basics
Everywhere an automation professional goes these days, it seems all they hear about is one of the keys to a company's success in this new automation age is being able to manage your supply chain. With a build to order philosophy in the industry, having the correct inventory at the facility at the correct time is vital to today's manufacturing processes.
But just how many people understand what supply chain management is all about?
Supply chain management handles all the storage and movements of raw materials, work-in-process inventory, and finished goods inventory from point of origin to point of consumption.
With effective and efficient supply chain management, a company can improve the way it finds the raw components it needs to make a product or service and deliver it to customers. While there is science involved, it is not all about manipulating a spreadsheet.
Planning is the strategic portion of supply chain management. A user needs a strategy for managing resources that go toward meeting customer demand for your product or service. A big piece of planning is developing a set of metrics to monitor the supply chain so it is efficient, costs less, and delivers high quality and value to customers.
Another important area is for the user to choose the suppliers that will deliver the goods and services needed to create the product. Develop a set of pricing, delivery and payment processes with suppliers, and create metrics for monitoring and improving the relationships. This is also a part of the collaboration process very popular in the industry these days. The user has to put together processes for managing the inventory of goods and services received from suppliers, including receiving shipments, verifying them, transferring them to manufacturing facilities, and authorizing supplier payments.
Once the inventory is there, the user has to schedule the necessities for production, testing, packaging, and preparation for delivery. This is the most metric-intensive portion of the supply chain, where the user can measure quality levels, production output, and worker productivity.
The next part of the supply chain is the logistics-the manufacturer coordinates the receipt of orders from customers, develops a network of warehouses, pick carriers to get products to customers, and sets up an invoicing system to receive payments.
The tail end of the chain is to create a network for receiving defective and excess products back from customers.
InTech Editor Gregory Hale compiled
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