Sergio Noto La Diega

An Object-Oriented Approach for Flexible Manufacturing Control Systems Analysis and Design Using the Unified Modeling Language

In reacting to global competition and rapidly changing customer demands, industrial business organizations have developed a strong interest in flexible automation. The aim of flexible automation focuses on achieving agility in handling uncertainties from internal or external environments. Modeling complex structures, promoting reuse, and shortening the development time cycle are particularly significant aspects in the analysis and design of CIM systems, where heterogeneous elements have to be integrated in a complex control architecture. The design methodology for FMS control software involves the abstraction of an FMS and the estimation of the system performances. The aim of this activity is to suggest the optimal configuration of an FMS for given specifications, through simulation tools. In the software engineering field, object-oriented (OO) approaches have proven to be a powerful technique with respect to such aspects. The unified modeling language (UML), by using OO design methodologies, can offer reusability, extendibility, and modifiability in software design. Also, it bridges the gap that exists between the OO analysis and design area and the area of OO programming by creating an integrative metamodel of OO concepts. The specific goal of this paper is to formulate a new methodology for developing reusable, extendible, and modifiable control software for an FMS in an object-oriented environment. It is demonstrated that, with few diagrams, UML can be used to model such systems without being associated with other modeling tools.

Long term capacity decisions in uncertain markets for advanced manufacturing systems incorporating scope economies

Abstract By examining the literature in the field of manufacturing flexibility many researchers have located several form of flexibility by distinguishing them into strategic and operational flexibility forms. Furthermore, many measures and design methods have been proposed for flexible manufacturing systems. Surely scope economies are one of the most important strategic form of flexibility in manufacturing systems and their strategic impact has been acknowledged by the very beginning of the flexible manufacturing era. However, despite several researches are available to address scope economies measurement and design methodologies, very few researches investigate their economic convenience in front of dedicated manufacturing systems depending on the competitive market conditions. This paper proposes a theoretical model whose main aim is the general understanding of the convenience conditions of scope economies-based manufacturing systems. The results of the theoretical model are very interesting, because they locate market conditions that make scope economies manufacturing systems less profitable than dedicated manufacturing ones; moreover, the proposed model sets some general criteria to guide the entrepreneur in making right investment decision regarding this kind of manufacturing investments. Such results can explain the reason of many failures of flexible manufacturing systems and it suggests the use of this kind of approach to investigate other flexibility forms of manufacturing systems. The ultimate goal of this research is the construction of a Decision Support System for supporting the entrepreneur in making decision on Advanced Manufacturing Systems investment decisions.

Strategic FMS design under uncertainty: A fuzzy set theory based model

Abstract Flexibility is assuming more and more relevance in the manufacturing strategy, because it allows to face the increasing uncertainty in which the firms are competing nowadays. In order to increase their strategic competitiveness, several firms in many industries are increasing their investment in Flexible Manufacturing Systems (FMS). In the first FMS design step the following decisions should be made: (a) flexibility level decision, i.e. how many kind of products the designing FMS has to produce; (b) size level decision, i.e. what is the aggregate volume the FMS can perform; (c) capacity definition decision, i.e. how many machines for each type have to be installed. These decisions are to be made under an uncertain design environment. The major uncertainty concerns the demand and the price for each product due to the market forecasts uncertainty, and the work-load characteristics (time and routing) of each product due to the product changes over the manufacturing system life cycle. The design objectives are the expected profit maximization and the investment risk minimization, trying to increase the flexibility level and to reduce the profits uncertainty. This paper proposes a fuzzy set theory multiple objectives model that is able to face the uncertainty in the design data determining the FMS configuration that optimizes the expected profits considering the entrepreneur risk propensity.