Decision-Modeling Components

The supply chain configuration hub provides means for collaborative exploration of the configuration problem from various views on the basis of the common information and knowledge basis. Ready-to-use software packages are used for implementation of many of the components. The key functions of the components are 

Model management component Experimental design Execution of experiments Orchestration of modeling activities Maintenance of modeling results 

Conceptual modeling application Creation and maintenance of concepmal models 

Data management component Offline data retrieval On-demand data retrieval Data maintenance Data transformation Data sharing 

Knowledge management application Maintenance of common dictionary Maintenance of best practices Maintenance of modeling templates 

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The objective of this chapter is to describe the application of conceptual modeling techniques for supply chain configuration purposes. The general approach is to use well-known conceptual and information modeling techniques that would enable potential model-driven implementation of decision-modeling components. 

The modeling technique specific models are developed on the basis of the general data model. Utilization of the general model is useful if multiple specific models need to be constructed. It is also important to enable data mapping between source information systems and decision-modeling components. 

This module permits the insertion, edition and exclusion of pipeline sections and hazardous or accidental scenarios which will be analyzed during the decisionmaking process. It will be clear, in this section, that this module consists on the base of data and information requisites necessaries to the effective use of the proposed DSS, because the decision model is completely dependent of the data and information proceeding of this two components of decision process the actions (sections) and the nature states (hazardous scenarios). 

They include the user as an integral part of the supply chain control system in their research test-bed. To this end, the simulation component dynamically generates live data, such as customer orders, to the ERP and SCM components. Then, the user makes decisions about the ERP and SCM systems to manage the supply chain. The system periodically gives feedback to the user and the rest of the model. Ball et al. intend to investigate both the performance of supply chain software and human decision-making. For more information about the model and how it relates to available-to-promise (ATP) decision models, refer to chapter 11. 

Implementation of decision-making components. If decision-making is to be performed routinely, a software application needs to be developed. Information modeling is an essential part of almost any software development project. 

Definition of links between decision-modeling and other parts of the enterprisewide information system. Decision-making models rely on data provided from other parts of the information system and can also use some functions provided by the supply chain information system. Information modeling is used to map data between components and identify available functions. 

In the case of implementation of decision-making components, information modeling methods are used in a similar manner as in the development of information systems. This approach is mainly applicable if decision- making components... 

Processors indicator model, deterioration model of critical components, risk based cost model and risk based decision model ... 

As illustrated in Figure 6, in order to develop an optimal O M model a risk based decision model and deterioration models of critical components should be developed. 

The system level consists of the system state, the system inspection and the decision model. System state depends on track component deterioration and system structure. Any component failure will lead to system failure state, thus system is considered to be a series system. A system inspection is... 

Proper assignment of tolerances is one of the least well-understood engineering tasks (Gerth, 1997). Assignment decisions are often based on insufficient data or incomplete models (Wu et al., 1988). The precise assignment of the component tolerances for this combined effect is multifarious and is dictated by a number of factors, including ... 

In order to analyze complex decision making tasks, HTA must be used in combination with various cognitive models of performance. Also HTA presents some limitations in describing tasks with a significant diagnostic component. 

These models, however, can be useful if estimates are to be made of operating costs. By assigning fixed and variable costs to each activity, average and marginal unit costs at each stage of the process can be easily calculated, which will assist in decisions regarding pricing policies or whether to buy in components and materials or make them on site. ATPLAN is an example of a network-based model of this type. 

There are some aspects of process design in which decisions are based primarily on past experience rather than on quantitative performance models. Problems of this type include the selection of constraction materials, the selection of appropriate models for evaluating the physical properties of homogeneous and heterogeneous mixtures of components, and the selection of safety systems. Advances in expert systems technology and information management will have a profound impact on expressing the solutions to these problems. 

The PLS algorithm is relatively fast because it only involves simple matrix multiplications. Eigenvalue/eigenvector analysis or matrix inversions are not needed. The determination of how many factors to take is a major decision. Just as for the other methods the right number of components can be determined by assessing the predictive ability of models of increasing dimensionality. This is more fully discussed in Section 36.5 on validation. 

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