Ayelet Gal-Tzur

Paradigms for knowledge-based systems in industrial engineering

Abstract When developing expert systems, expertise lies not only in formulating the knowledge to be put into the knowledge base, but also in deciding upon the knowledge representation and inference mechanism most suited to the application. Six detailed knowledge bases demonstrate the application of various AI-based systems to industrial engineering problems. They illustrate a number of approaches: expert systems, which are based upon practical experience; decision systems, which derive from modelling skills; and situation-action systems, which rely on production process design skills. The six paradigms presented describe a logical expert system for selecting material handling equipment; a multi-valued expert system for selecting a dispatching rule for automatic guided vehicles; a profile matching expert system for selecting project management software; a confidence building expert system for selecting a machine feeder; a tandem decision system for developing a production schedule; and a situation-action system for controlling job allocation in a flexible manufacturing cell. The relationships between these various paradigms and the characteristics of problems to which they can be applied are categorized by the nature of the expert and his expertise; the features of the environment; the decision or decisions to be taken; and the manner in which AI-system performance can be evaluated. A knowledge base is proposed for determining which architecture is most appropriate for a given application.

Transport Policy: Social Media and User-Generated Content in a Changing Information Paradigm

Rapid and recent developments in social media networks are providing a vision amongst transport suppliers, governments and academia of ‘next-generation’ information channels. This chapter identifies the main requirements for a social media information harvesting methodology in the transport context and highlights the challenges involved. Three questions are addressed concerning (1) The ways in which social media data can be used alongside or potentially instead of current transport data sources, (2) The technical challenges in text mining social media that create difficulties in generating high quality data for the transport sector and finally, (3) Whether there are wider institutional barriers in harnessing the potential of social media data for the transport sector. The chapter demonstrates that information harvested from social media can complement, enrich (or even replace) traditional data collection. Whilst further research is needed to develop automatic or semi-automatic methodologies for harvesting and analysing transport-related social media information, new skills are also needed in the sector to maximise the benefits of this new information source.

Frame-based architectures for manufacturing planning and control

Abstract Effective manufacturing planning and control (MPC) necessitates coordination and integration of various aspects of demand, production and logistics management. A holistic approach is therefore the key to success in this field. A frame-based architecture should be ideally suited to constructing knowledge-based systems for MPC, as frames can represent entities in the planning process, rules can express interrelationships between these entities, and the planning strategy is paralleled by the inference procedure. Four applications are described in detail by means of four frame-based paradigms: design of an operations regime; project planning of a new product launch; configuration of a process cell; and an analysis of the operation of an integrated manufacturing system. These architectures, and others presented in a previous article, are categorized as examples of generic tasks , a methodology proposed by Chandrasekaran 12 which defines underlying structures in terms of system goals, input/output characteristics, knowledge representation and inference strategy. The generic task approach appears to be useful in determining an appropriate architecture for a given MPC task, and also for designing and implementing the resultant knowledge-based system.