Development of Manufacturing Cells Using an Artificial Ant-Based Algorithm with Different Similarity Coefficients

Although there exists several ways of solving the cellular manufacturing problem, including several ant-based algorithms, many of these algorithms focus on obtaining the best possible answer instead of efficiency. An existing artificial-ant based algorithm AntClass, was modified so that it is easier to manipulate. AntClass uses Euclidean vectors to measure the similarity between parts, because similarity is used to group parts together instead of distances, the modified version uses similarity coefficients. The concept of heaping clusters was also introduced to ant algorithms for cellular manufacturing. Instead of using Euclidean vectors to measure the distance to the center of a heap, as in the AntClass algorithm, an average similarity was introduced to measure the similarity between a part and a heap. The algorithm was tested on five common similarity coefficients to determine the similarity coefficient which gives the better quality solution and the most efficient process

Embedded Multi-Agent Systems Based Wireless Control Networks for Cyber-Physical Systems

With the emergence of cyber-physical systems, there has been a growing interest in network-connected cyber-physical devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. As the capabilities of low processing power devices increase, there is also a growing interest in wireless control networks. As the capabilities of wireless control networks are extended to reconfigurable systems, the bandwidth requirements are drastically increasing. To remain reconfigurable, an intelligent entity needs to process all of this data. Intelligent models are typically deployed in a cloud environment, and required data (typically sensory and reconfiguration data) is passed through a series of network protocols (eg. wireless sensor network and internet protocols) where it is then aggregated and processed by a model, which then returns reconfiguration data and control instructions. For large-scale industrial networks however, the limit on bandwidth produces a challenge for employing intelligent cloud-based models. In this thesis, embedded intelligence in wireless control networks by means of embedded software agents is proposed. Through the use of wireless sensor communication protocols based off of hardware protocols such as ZigBee, the embedded agents are proposed to maintain intelligence while reducing the bandwidth requirements of the wireless control network. Architectures for both cloud-based and embedded agents are compared through an experiment and simulation, which shows the embedded agents are still able to maintain the same quality of service while reducing the bandwidth usage. As the goal of embedding agents is to maintain the intelligence of the wireless control network in a more distributed fashion, new wireless protocols need to be developed. In harsh industrial environments, the wireless control network is subject to blockages, such as interference from welding machines. In this thesis, two prescriptive reconfiguration protocols to overcome such harshness are proposed. The first reconfiguration protocol aims to overcome blockage between the individual sensing/acting nodes and the sink, which is responsible for aggregating and transmitting data to a data acquisition system. The second reconfiguration protocols are meant to overcome blockage between sensor nodes and actor nodes handling the same process. Both reconfiguration protocols are detailed, and tested in an experimental simulation. The results of the experiment show that when there is either type of blockage, the quality of service remains the same. The only significant effect is seen on process-level metrics when there is blockage between the sensor and actor nodes of the same process

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network