10615305
Manufacturing sypply chain management: distributed supply chain simulation across enterprise boundaries
The effective practice of supply chain management (SCM) is crucial to improve corporations' competitive advantage. Many corporations have built simulation models to facilitate the application of simulation in designing, evaluating, and optimizing their supply chain. Traditionally, a supply chain involves only a single enterprise with multiple facilities and distribution centers. Hence, sharing of detailed simulation models is not a problem in this scenario. But in recent years, the scope of SCM has evolved to cross the enterprise boundaries. Applying simulation in designing, evaluating, and optimizing the supply chain becomes more difficult since the participating corporations might not be willing to share their simulation models with partners. In this paper, distributed simulation techniques are presented as an enabling technology that allows corporations to construct a cross enterprise simulation while hiding model details within the enterprise. This can be realized by either building the simulation on top of the Runtime Infrastructure of the High Level Architecture or building the simulation on top of a customized distributed discrete event simulation protocol. These alternative approaches are compared in terms of their performance and interoperability. The comparison of the performance is done through a benchmarking test of a semiconductor supply chain model.
32884753
Expert Simulation For On-line Scheduling
In recent years, the automotive industry has realized the importance of speed of new products to market and has mounted efforts for improving it. The Expert System Scheduler (ESS) facilitates these efforts by enabling manufacturing plants to generate viable schedules under increasing constraints and demands for flexibility. The scheduler takes advantage of the Computer Integrated Manufacturing (CIM) environment by utilizing the real-time information from the factory for responsive scheduling. The Expert System Scheduler uses heuristics developed by an experiences factory scheduler. It uses simulation concepts and these heuristics to generate schedules. Forward and "backward" simulation are used at different stages of the schedule generation process. The system is used to control parts flow on the factory floor at one automated facility. This highly automated facility is a testbed for implementation of CIM concepts. The scheduler runs on a Texas Instruments (TI) Explorer II computer using software developed inhouse utilizing IntelliCorp's Knowledge Engineering Environment (KEE) shell and the LISP language. The scheduling computer is networked to the factory control computer, which actually controls the plant floor. The TI Explorer II acquires current plant floor information from the factory control system, generates a new schedule and sends it back within a short time. The configuration allows fast response to changes in requirements and plant floor conditions.
18971661
Development of a high-level supply chain simulation model
This paper describes an effort that involved development of a simulation model for evaluating the business processes and inventory control parameters of a logistics and distribution supply chain. A generic simulation tool, rather than a supply chain simulator, was developed for meeting customized needs of the effort. The paper describes, the approaches used to model at the selected level of abstraction, the development of interfaces for data and experimentation and the development and delivery of animation for communicating the approach and results to the client.
18211780
Supply chain opportunities: panel session: opportunities for simulation in supply chain management
It has become a matter of survival that many companies improve their supply chain efficiency. This presents an opportunity for simulation. However, there are many challenges that must be overcome for simulation to be a contributor to play an effective role. Four contributors discuss the opportunities that they see for simulation to play a meaningful role in the area of supply chain management.
201885623
Manufacturing supply chain applications: modeling computer assembly operations for supply chain integration
Factory operations have been modeled for years to understand the relationship between the different design and policy factors and the performance measures of interest. The increasing awareness of the need to manage factories as a link in the supply chain places a corresponding requirement for an enhanced approach for factory modeling. This paper describes the modeling of a computer assembly factory for supply chain integration by including aspects of inbound and outbound logistics and relevant business processes. Lessons are drawn based on the experience.
6477912
Stress testing a supply chain using simulation
Simulation provides the capability to evaluate performance of a system operating under current or proposed configurations, policies and procedures. It is very applicable to evaluation of strategic and operational level plans for supply chains. It is especially useful for exploring the viability of a supply chain before beginning production. This paper describes the use of simulation for determining the readiness of a supply chain designed by a small company for providing sub-systems to a defense contractor. The supply chain had to be stress tested at surge and mobilization volume levels to meet the requirements. Simulation provided the ideal methodology to identify and demonstrate the behavior of the supply chain under stress and evaluate strategies to meet the defined volumes. It was used to prove the readiness of the supply chain reducing perceived risks in using the virtual operation.
12629185
Some Recent Results in U-Shaped Learning
U-shaped learning deals with a learner first having the correct hypothesis, then changing it to an incorrect hypothesis and then relearning the correct hypothesis. This phenomenon has been observed by psychologists in various studies of children development. In this survey talk, we will discuss some recent results regarding U-shaped learning and related criteria.
12002929
Prescribed Learning of R.E. Classes
This work extends studies of Angluin, Lange and Zeugmann on the dependence of learning on the hypotheses space chosen for the class. In subsequent investigations, uniformly recursively enumerable hypotheses spaces have been considered. In the present work, the following four types of learning are distinguished: class-comprising (where the learner can choose a uniformly recursively enumerable superclass as hypotheses space), class-preserving (where the learner has to choose a uniformly recursively enumerable hypotheses space of the same class), prescribed (where there must be a learner for every uniformly recursively enumerable hypotheses space of the same class) and uniform (like prescribed, but the learner has to be synthesized effectively from an index of the hypothesis space). While for explanatory learning, these four types of learnability coincide, some or all are different for other learning criteria. For example, for conservative learning, all four types are different. Several results are obtained for vacillatory and behaviourally correct learning; three of the four types can be separated, however the relation between prescribed and uniform learning remains open. It is also shown that every (not necessarily uniformly recursively enumerable) behaviourally correct learnable class has a prudent learner, that is, a learner using a hypotheses space such that it learns every set in the hypotheses space. Moreover the prudent learner can be effectively built from any learner for the class.
2236374
Finite learning by a “team”
6600546
Learning and Extending Sublanguages
A number of natural models for learning in the limit is introduced to deal with the situation when a learner is required to provide a grammar covering the input even if only a part of the target language is available. Examples of language families are exhibited that are learnable in one model and not learnable in another one. Some characterizations for learnability of algorithmically enumerable families of languages for the models in question are obtained. Since learnability of any part of the target language does not imply monotonicity of the learning process, we consider also our models under additional monotonicity constraint.
30237295
Crowd Control: Coordinating Processes in Parallel
Tutorials • Bridget Rosewell and Paul Ormerod " Agent Based Models and Social Simulation in the Policy Process " [Room: Aula Magna] This tutorial will focus on practical examples of agent based models which are actually being used as part of the decision making process of policy makers. The tutorial will also address key issues in integrating ABMs and social simulation into the policy making process. The tutorial will introduce the Multi-Agent Simulation Suite (MASS), a novel, integrated simulation environment for agent-based social simulation. MASS was designed with scientific modelers and not professional programmers in mind. Therefore, ease of use and prudent scientific practices were at the focus of the suite's design. The tutorial consists in a brief introductory part providing a generalized definition of the basic elements composing a simulation model. Then, it will be shown how LSD allows users to transparently adopt the theoretical definition, automatically generating all the technical code necessary for developing, running and analysing a simulation model. A series of examples will show the advantages of the definition proposed and the most relevant features of LSD. The tutorial will introduce the Multi-Agent Simulation Suite (MASS), a novel, integrated simulation environment for agent-based social simulation. MASS was designed with scientific modelers and not professional programmers in mind. Therefore, ease of use and prudent scientific practices were at the focus of the suite's design.