195865607
Experiences With Backward Simulation Based Approach For Lot Release Planning
Bottleneck based scheduling approach suggests planning the release of lots based on the capacity of the bottleneck machines in the manufacturing process. Many scheduling systems determine the start of the first operation of the lot based on backward scheduling from its operation on the bottleneck machine. An approach was developed for determining the lot release times based on backward simulation. While conceptually appealing and successful with simple problems, the approach did not lead to expected improvements in a highly complex semiconductor manufacturing scenario. This paper describes the approach, its implementation and the limitations realized in the complex scenario.
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.
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.
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.
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.
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.
2098994
Learning in the presence of inaccurate information
Abstract The present paper considers the effects of introducing inaccuracies in a learner's environment in Gold's learning model of identification in the limit. Three kinds of inaccuracies are considered: presence of spurious data is modeled as learning from a noisy environment, missing data is modeled as learning from incomplete environment, and the presence of a mixture of both spurious and missing data is modeled as learning from imperfect environment. Two learning domains are considered, namely, identification of programs from graphs of computable functions and identification of grammars from positive data about recursively enumerable languages. Many hierarchies and tradeoffs resulting from the interplay between the number of errors allowed in the final hypotheses, the number of inaccuracies in the data, the types of inaccuracies, and the type of success criteria are derived. An interesting result is that in the context of function learning, incomplete data is strictly worse for learning than noisy data.
45469476
Predictive learning models for concept drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the concept shifts may not have to satisfy any further requirements and may occur infinitely often. Within this work is studied to what extent it is still possible to predict or learn values for a data sequence produced by drifting concepts. Various ways to measure the quality of such predictions, including martingale betting strategies and density and frequency of correctness, are introduced and compared with one another. For each of these measures of prediction quality, for some interesting concrete classes, usefully established are (nearly) optimal bounds on permanence for attaining learnability. The concrete classes, from which the drifting concepts are selected, include regular languages accepted by finite automata of bounded size, polynomials of bounded degree, and exponentially growing sequences defined by recurrence relations of bounded size. Some important, restricted cases of drifts are also studied, e.g., the case where the intervals of permanence are computable. In the case where the concepts shift only among finitely many possibilities from certain infinite, arguably practical classes, the learning algorithms can be considerably improved.
26889483
Ordinal Mind Change Complexity of Language Identification
The approach of ordinal mind change complexity, introduced by Freivalds and Smith, uses constructive ordinals to bound the number of mind changes made by a learning machine. This approach provides a measure of the extent to which a learning machine has to keep revising its estimate of the number of mind changes it will make before converging to a correct hypothesis for languages in the class being learned. Recently, this measure, which also suggests the difficulty of learning a class of languages, has been used to analyze the learnability of rich classes of languages. Jain and Sharma have shown that the ordinal mind change complexity for identification from positive data of languages formed by unions of up to n pattern languages is ωn. They have also shown that this bound is essential. Similar results were also established for classes definable by length-bounded elementary formal systems with up to n clauses. These later results translate to learnability of certain classes of logic programs.
145211
Computational Limits on Team Identification of Languages
A team of learning machines is a multiset of learning machines. A team is said to successfully identify a concept just in case each member of some nonempty subset, of predetermined size, of the team identifies the concept. Team identification of programs for computable functions from their graphs has been investigated by Smith. Pitt showed that this notion is essentially equivalent to function identification by a single probabilistic machine. The present paper introduces, motivates, and studies the more difficult subject of team identification of grammars for languages from positive data. It is shown that an analog of Pitt's result about equivalence of team function identification and probabilistic function identification does not hold for language identification, and the results in the present paper reveal a very complex structure for team language identification. It is also shown that for certain cases probabilistic language identification is strictly more powerful than team language identification. Proofs of many results in the present paper involve very sophisticated diagonalization arguments. Two very general tools are presented that yield proofs of new results from simple arithmetic manipulation of the parameters of known ones.
28735249
On Monotonic Strategies for Learning r.e. Languages
Overgeneralization is a major issue in identification of grammars for formal languages from positive data. Different formulations of monotonic strategies have been proposed to address this problem and recently there has been a flurry of activity investigating such strategies in the context of indexed families of recursive languages.