Reference architecture for holonic manufacturing systems: PROSA
Computers in Industry - Special issue on manufacturing systems
Simulation Made Easy: A Manager's Guide
Simulation Made Easy: A Manager's Guide
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Agent Based Manufacturing
Inference based on notifications: a holonic metamodel applied to control issues
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Building a Holarchy Using Business Process-Oriented Holonic (PrOH) Modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Optimization Models for Training Belief-Rule-Based Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Verification of Knowledge-Based Systems Using Predicate/Transition Nets
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
FuzzyShell: a large-scale expert system shell using fuzzy logic for uncertainty reasoning
IEEE Transactions on Fuzzy Systems
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Current production leanings, such as high product variability, demand advanced manufacturing systems (MSs). An example is the holonic MS (HMS) in which entities (e.g., resources and products) are "smart." These entities are called holons (HLs), and their interactions are coordinated by holonic control (HC). Indeed, the complexity of HMS has required new design and test tools. In this context, this paper presents an HC metamodel, which was applied to a particular simulator. In this control solution, causal knowledge is enclosed in Rule HLs, which receive facts about Resource HLs and deliberate about the actions to be executed. The inference happens by means of an innovative net of notifications built from expert knowledge, in the form of (Sub)-HLs, which allows high reactivity, HL decoupling, conflict handling, coherent control expression and execution, and easy control adaptations. This solution still considers other issues, namely, the product-driven manufacturing: a tendency related to customized production in which Product HLs negotiate with Resource HLs aiming at adaptability and reactivity. In this case, Rule HLs intermediate and organize the collaborations of Product HLs and Resource HLs. This paper proposes to use the metamodel to compose a process-driven control and a product-driven control applied to a similar simulated HMS, highlighting their differences and advantages.