Conflict and error management: A case in the furniture industry

The purpose of this study is to investigate and provide tools for the furniture industry, for detecting and preventing damage from propagating errors. Many of the errors cascading in a furniture manufacturing facility are typically detected only after the original process that causes the error had already caused errors. Previous research has developed and validated theoretical methods, such as CEPD, to prevent and detect errors and conflicts. This thesis is the first effort to implement the logic of CEPD in the furniture industry. There are four relevant measures that are analyzed and improved in this thesis; they are preventability, reliability, damage, and time to completion. The study proposed an Efficient inspection assigning method that is based on Centralized and Decentralized strategy. The efficient inspection method increases performance by reducing the working time and maintains the preventability and reliability of the system. The method was validated for a case of laminating department of a furniture industry. A total of eighteen scenarios for the case were analyzed and simulated using ARENA simulation. For comparison, each simulation result scenario went through pairwise t-test. The significance test shows the new Efficient inspection method can maintain preventability and reliability with lower working time: On average, reliability was increased by 0.54% with standard deviation 0.09%; working time was reduced on averaged by 5.54% with standard deviation of 2.13%. Both improvements are directly realized by error and conflict prevention. Future research will address hybrid decentralized/centralized system optimization on performance without deteriorating reliability. Useful observations were also found that can lead to improvements in the CEPD logic

Comodo: Collaborative Monitoring of Commitment Delegations

Understanding accountability in contract violations, e.g., whom is accountable for what, is a tedious, time-consuming, and costly task for human decision-making, especially when contractual responsibilities are delegated among parties. Intelligent software agents equipped with expert capabilities such as monitoring and diagnosis help save time and improve accuracy of diagnosis by formal reasoning upon electronic contracts. Such contracts are represented as commitment norms, a well studied artifact in multi-agent systems, which provide semantics for agent interactions. Due to the open and heterogeneous nature of multi-agent systems, commitments are often violated. When a commitment is violated, e.g., an exception occurs, agents need to collaborate to understand what went wrong and which agent is responsible. We propose Comodo: a framework for monitoring commitment delegations and detecting violations. We define a complete set of possible rational delegation schemes for commitments, identifying for each combination of delegations what critical situations may lead to an improper delegation and potentially to a commitment violation. Comodo provides a sound and complete distributed reasoning procedure that is able to find all improper delegations of a given commitment. We provide the complete implementation of Comodo using the Reactive Event Calculus, and present an e-commerce case study to demonstrate its workings. Due to its generic nature, we discuss the application of our approach to other distributed diagnosis problems in emergency healthcare, Internet of Things and smart environments, and security, privacy, and accountability in the context of socio-technical system