Abstract Interpretation with Unfoldings

We present and evaluate a technique for computing path-sensitive interference conditions during abstract interpretation of concurrent programs. In lieu of fixed point computation, we use prime event structures to compactly represent causal dependence and interference between sequences of transformers. Our main contribution is an unfolding algorithm that uses a new notion of independence to avoid redundant transformer application, thread-local fixed points to reduce the size of the unfolding, and a novel cutoff criterion based on subsumption to guarantee termination of the analysis. Our experiments show that the abstract unfolding produces an order of magnitude fewer false alarms than a mature abstract interpreter, while being several orders of magnitude faster than solver-based tools that have the same precision.Comment: Extended version of the paper (with the same title and authors) to appear at CAV 201

Multiscale Design for Solid Freeform Fabrication

One of the advantages of solid freeform fabrication is the ability to fabricate complex structures on multiple scales, from the macroscale features of an overall part to the mesoscale topology of its internal architecture and even the microstructure or composition of the constituent material. This manufacturing freedom poses the challenge of designing across these scales, especially when a part with designed mesostructure is part of a larger system with changing requirements that propagate across scales. A setbased multiscale design method is presented for coordinating design across scales and reducing iterative redesign of SFF parts and their mesostructures. The method is applied to design a miniature unmanned aerial vehicle system. The system is decomposed into disciplinary subsystems and constituent parts, including wings with honeycomb mesostructures that are topologically tailored for stiffness and strength and fabricated with selective laser sintering. The application illustrates how the design of freeform parts can be coordinated more efficiently with the design of parent systems.Mechanical Engineerin

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Modelling the evolution of uncertainty levels during design

Design work involves uncertainty that arises from, and influences, the progressive development of solutions. This paper analyses the influences of evolving uncertainty levels on the design process. We focus on uncertainties associated with choosing the values of design parameters, and do not consider in detail the issues that arise when parameters must first be identified. Aspects of uncertainty and its evolution are discussed, and a new task-based model is introduced to describe process behaviour in terms of changing uncertainty levels. The model is applied to study two process configuration problems based on aircraft wing design: one using an analytical solution and one using Monte-Carlo simulation. The applications show that modelling uncertainty levels during design can help assess management policies, such as how many concepts should be considered during design and to what level of accuracy.This is the author accepted manuscript. The final version is available from Springer via http://www.springerlink.com/content/p17w476671110704

Agent-Based Product Configuration: towards Generalized Consensus Seeking

This paper will present an evolution of a fuzzy agent based platform which performed products configuration. As a first step, we used the notion of consensus to establish robust results at the end of the configuration process. We implemented the concept of generalized consensus which implied the consideration of consensuses from the beginning, in this way robust data are treated during the entire process and the final result enables the designer to distinguish the robust components and flexible ones in a set of configurations.Comment: 8 pages, 8 figures, 5 table