Preactor Planning and Scheduling Software for Enterprise Application

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1 Preactor Planning and Scheduling Software for Enterprise Application Gregory Quinn President, Quinn & Associates Inc Vice President North America, Preactor International Ltd. Introduction The scope of this document is to discuss the options in using Preactor software products for enterprise-wide use. For purposes of this paper, the term enterprise means a collection of multiple sites that benefit from some degree of centralized management. Each site may have additional information that modifies or augments the plan generated by corporate. Within this context, several system architectures arise that will influence the deployment and use of Preactor software products. This paper will examine each case and describe the Preactor license topology that forms the most effective solution. It is outside the scope of this paper to examine the merits of each ERP structure. The system architecture used to illustrate concepts will be a 2 tier structure comprised of a corporate layer as the management level and a site layer representing the plants in a multi-site enterprise. N-tier architectures can be extended from the basic concepts presented in this paper. The Preactor family of solutions is quite broad, offering a great deal of flexibility in solving scheduling problems. For this paper, the solutions will be generalized to a planning configuration and a scheduling configuration to highlight the role each solution plays in the suite of software for the enterprise. Glossary APS Advanced planning and scheduling. Effective APS systems are built upon FCS engines. Corporate The controlling layer of the enterprise. The degree of control on the sites by centralized planning may be lax or tight. Enterprise A manufacturing company with multiple sites making either same or different product. For purposes of this paper the enterprise consists of a one corporate node and multiple manufacturing sites. ERP Enterprise resource planning. FCS Finite capacity scheduling. Scheduling engines that model any number of constraints to represent the production environment and maximize production performance against one or more goals. GMPS Graphic MPS. This is a configuration of the Preactor APS.

2 MO Manufacturing order. Contained within the manufacturing order may be routing steps and resource requirements to produce the product. MPS Master production scheduling. Demand is consolidated into production targets per period of time. MRP Materials requirement planning Site A manufacturing facility Supply Chain Execution - The compliment to the supply chain planning function, SCE includes the specific instruction set for the nodes within the supply chain to effectively implement the supply chain plan Work center Either a single manufacturing resource or a collection or resources (department, line or cell) Case 1: Centralized MRP In this structure, not only is planning executed at the corporate layer, also the generation of manufacturing orders (MO s) are passed from a central MRP function to each site. The sites receive MO s from corporate, and then operate to fulfill the specific demand based on guidance in the form of priority of each order or some other scheduling goal established at the local level. Performance against MO is reported from site back to corporate. Product definitions in the form of routings may be maintained locally or at corporate. See Figure 1. Within this schema, corporate is exercising tight planning control on each site. Therefore the scheduling system has a primary purpose of meeting the local scheduling objectives in the face of what may be a very dynamic and disembodied ordering environment. The span of the Preactor scheduling model will be at the site level, which is to say that the scheduling model will represent the site resources to a sufficient degree that the scheduling objections for the site can be met. The model may be a mix of

3 specific machines, work cells, departments, or subcontractors. Each scheduling system is decoupled and is unaware of the decisions made by the other scheduling systems. Case 2: Centralized Demand Planning; Local MRP In this structure, demand is allocated by site from a centralized planning function to each site, and each site executes MRP to generate MOs. Product definitions are maintained locally. Performance against MOs is reported locally, but performance against demand targets is reported from each site to corporate. The production targets established by corporate arise from a planning process that may be largely unconstrained, or generally constrained at best, and may be subject to adjustment as site feedback from the local MRP run indicates capacity restrictions that modify production targets previously set by corporate. Fundamentally the architecture is the same as that shown in Figure 1. However with the degree in freedom of local MRP in this case, each site may have the option to treat other sites as suppliers of parts or finished goods. The Preactor Communications Object (PCO) allows Preactor scheduling systems to communicate with one another to determine available capacity. Figure 2 reflects the added capability. There are implications with PCO for supply chain execution (SCE), and those will be addressed in a later section. Case 3: Centralized Scheduling In this architecture, corporate maintains a global scheduling model incorporating all resources at each site. Information in the form of dispatch lists is sent to each work center at each site from corporate. Work center performance is reported directly to corporate. This architecture has greater resource control than Case 1, and is often encountered in process industries with large scale production of products that are used as components inside and outside the enterprise. Figure 3 shows the flow of information for this case.

4 In the previous cases, scheduling rules would generally reflect site-level business objectives. For this case, SCE rules can be integrated into the multi-site model to better optimize the allocation of demand to each site and the site-to-site interaction when the limits of specific-site capacity are reached. The rules can include logistical elements that trade off cost of production at a site and the cost to transport finished goods to a customer, distribution center, or another site within the enterprise. This is not to say that this is the only architecture that SCE rules can be implemented. In the following section the introduction of Preactor Graphical Master Production Scheduling (GMPS) offer options that can be applied in all architectures. Planning and Supply Chain Execution In each case cited, there is the option to use the Preactor GMPS model where the MPS module of the ERP system would be deployed. Figure 4 shows the general application of GMPS within the ERP system. The GMPS can be integrated with the Preactor scheduling model such that the feedback from the FCS calibrates the capacity constraints within the planning tool to improve the accuracy of the planning. It is important to note that the GMPS is a configuration of the Preactor APS, and the feature to create custom rules is preserved in the GMPS. It is worth noting the APICS definition of supply chain execution: Execution-oriented software applications for effective procurement and supply of goods and services across a supply chain. It includes manufacturing, warehouse, and transportation executions systems, and systems providing visibility across the supply chain. (APICS dictionary 12 th Ed.) While cases 1 and 2 are more rooted in meeting demand within a manufacturing environment, case 3 opens the possibility of adding any resource in the supply chain, and providing visibility of any and all resources as performance information is posted. For the Preactor applications, any resource can be modeled, and Preactor has been used to model distribution and transportation systems. Therefore within the definition presented, Preactor software can be extended beyond FCS/APS to SCE.

5 By placing the SCE rules at this layer of the architecture offers a number of advantages. There is an implicit concurrency in decision making in that the planner can make a higher level set of supply chain decisions without interfering with the operational scheduling decisions. Conversely the response time of the scheduling system is improved by removing SCE logic from the scheduling rules and possibly minimizing the site-to-site communications via PCO. Another advantage is that the maintenance of the planning and SCE rules involves only GMPS and therefore changes in the big picture business logic do not necessarily require additional maintenance of the site-level scheduling model. Communications between planner and scheduler are facilitated through the common application framework. Final Comments As with any discussion dealing with generalities, there can be overlaps between the three cases presented herein and variations as to the implementation and use of Preactor would be adopted to these changes. One of the key features of the Preactor family of planning and scheduling solutions is its adaptability ranging from basic shop floor scheduling to master production scheduling to supply chain execution. At each of these crucial elements in the enterprise software architecture, Preactor contributes a common look-and-feel as well as an unlimited modeling capability to tackle any level of abstraction of the production environment with a minimum software life cycle cost. With the improvements in efficiencies documented in over 15 years, Preactor can deliver the best return on investment for automation technology at site-level or enterprise-wide application.

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