Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets

Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Methods: Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Results: Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). Conclusion: The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller

Effects of Communication Protocol Stack Offload on Parallel Performance in Clusters

The primary research objective of this dissertation is to demonstrate that the effects of communication protocol stack offload (CPSO) on application execution time can be attributed to the following two complementary sources. First, the application-specific computation may be executed concurrently with the asynchronous communication performed by the communication protocol stack offload engine. Second, the protocol stack processing can be accelerated or decelerated by the offload engine. These two types of performance effects can be quantified with the use of the degree of overlapping Do and degree of acceleration Daccs. The composite communication speedup metrics S_comm(Do, Daccs) can be used in order to quantify the combined effects of the protocol stack offload. This dissertation thesis is validated empirically. The degree of overlapping Do, the degree of acceleration Daccs, and the communication speedup Scomm characteristic of the system configurations under test are derived in the course of experiments performed for the system configurations of interest. It is shown that the proposed metrics adequately describe the effects of the protocol stack offload on the application execution time. Additionally, a set of analytical models of the networking subsystem of a PC-based cluster node is developed. As a result of the modeling, the metrics Do, Daccs, and Scomm are obtained. The models are evaluated as to their complexity and precision by comparing the modeling results with the measured values of Do, Daccs, and Scomm. The primary contributions of this dissertation research are as follows. First, the metric Daccs and Scomm are introduced in order to complement the Do metric in its use for evaluation of the effects of optimizations in the networking subsystem on parallel performance in clusters. The metrics are shown to adequately describe CPSO performance effects. Second, a method for assessing performance effects of CPSO scenarios on application performance is developed and presented. Third, a set of analytical models of cluster node networking subsystems with CPSO capability is developed and characterised as to their complexity and precision of the prediction of the Do and Daccs metrics

Middleware control systems design and analysis using message interpreted Petri Nets (MIPN)

Many distributed frameworks use a message-oriented middleware to interchange information among several independent distributed modules. Those modules make up complex systems implementing basic actions and reporting events about their state. This paper introduces the Message Interpreted Petri Net (MIPN) model to design, analyze, and execute the central control of these middleware systems. The MIPN is a new Petri net extension that adds message-based high-level information communications and hierarchic capabilities. It also contributes to the definition and study of new properties such as terminability for the hierarchy-wide analysis of a system. Special attention is given to the analyzability of the model. Useful relations between the individual properties of each MIPN and the global properties of a hierarchic MIPNs system are extracted through a mathematical analysis of the model. The goal is to analyze each net separately and then build up the properties of the whole system. This results in a great aid for the programmer and optimizes the development process. This paper also shows the actual integration of this new MIPN model in different robot control frameworks to design, analyze, execute, monitor, log, and debug tasks in such heterogeneous systems. Finally, some applications created with this framework in the fields of robotics, autonomous vehicles, and logistics are also presentedMinisterio de Ciencia e Innovación | Ref. EXP00139978CER-2021100

AN INFORMATION MODEL IN THE DOMAIN OF DISASSEMBLY PLANNING FOR SUSTAINABLE MANUFACTURING

Disassembly, a process of separating the End of Life (EOL) product into discrete components for re-utilizing their associated residual values, is an important part for the sustainable manufacturing. This work focuses on the modeling of the disassembly planning related information, and develops a Disassembly Information Model (DIM) based on an extensive investigation of various informational aspects of the disassembly planning. The developed Disassembly Information Model, which represents an appropriate systematization and classification of the products, processes, uncertainties and degradations related information, follows a layered modeling methodology. In this layered configuration, the DIM is subdivided into three distinct layers with an intent to separate general knowledge into different levels of abstractions, and to reach a balance between information reusability and information usability. The performance evaluation of the DIM (usability and reusability) is accessed by successful implementations of the DIM model into two prototype software applications in the domain of disassembly planning. The first application, called the Disassembly Sequence Generator (DSG), identifies the optimal disassembly sequence using a CAD based searching algorithm and a disassembly Linear Programming (LP) model. The searching process results in an AND/OR graph, which represents all the feasible disassembly sequences of a specific EOL product; whereas the LP model takes the AND/OR graph as an input and determines the economically optimal process sequence among all the possibilities. The second application is called the Adaptive Disassembly Planning (ADP), which further takes the EOL product uncertainty and degradation issues into consideration. In order to address these issues, fuzzy logic and Bayesian Network methodologies are used to develop a Disassembly Decision Network (DDN), which adaptively generates the optimal disassembly sequence based on the current available information. This research work is the first attempt to develop a comprehensive Information Model in the domain of disassembly planning. The associated modeling methodology that has been developed in this research is generic and scalable, and it could be widely adopted in other engineering domains, like product assembly, production planning, etc. The ultimate objective of this work is to standardize the DIM into a reference model that will be acknowledged and agreed upon by the sustainable manufacturing community

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

This thesis considers an application of a temporal theory to describe and model the patient journey in the hospital accident and emergency (A&E) department. The aim is to introduce a generic but dynamic method applied to any setting, including healthcare. Constructing a consistent process model can be instrumental in streamlining healthcare issues. Current process modelling techniques used in healthcare such as flowcharts, unified modelling language activity diagram (UML AD), and business process modelling notation (BPMN) are intuitive and imprecise. They cannot fully capture the complexities of the types of activities and the full extent of temporal constraints to an extent where one could reason about the flows. Formal approaches such as Petri have also been reviewed to investigate their applicability to the healthcare domain to model processes. Additionally, to schedule patient flows, current modelling standards do not offer any formal mechanism, so healthcare relies on critical path method (CPM) and program evaluation review technique (PERT), that also have limitations, i.e. finish-start barrier. It is imperative to specify the temporal constraints between the start and/or end of a process, e.g., the beginning of a process A precedes the start (or end) of a process B. However, these approaches failed to provide us with a mechanism for handling these temporal situations. If provided, a formal representation can assist in effective knowledge representation and quality enhancement concerning a process. Also, it would help in uncovering complexities of a system and assist in modelling it in a consistent way which is not possible with the existing modelling techniques. The above issues are addressed in this thesis by proposing a framework that would provide a knowledge base to model patient flows for accurate representation based on point interval temporal logic (PITL) that treats point and interval as primitives. These objects would constitute the knowledge base for the formal description of a system. With the aid of the inference mechanism of the temporal theory presented here, exhaustive temporal constraints derived from the proposed axiomatic system’ components serves as a knowledge base. The proposed methodological framework would adopt a model-theoretic approach in which a theory is developed and considered as a model while the corresponding instance is considered as its application. Using this approach would assist in identifying core components of the system and their precise operation representing a real-life domain deemed suitable to the process modelling issues specified in this thesis. Thus, I have evaluated the modelling standards for their most-used terminologies and constructs to identify their key components. It will also assist in the generalisation of the critical terms (of process modelling standards) based on their ontology. A set of generalised terms proposed would serve as an enumeration of the theory and subsume the core modelling elements of the process modelling standards. The catalogue presents a knowledge base for the business and healthcare domains, and its components are formally defined (semantics). Furthermore, a resolution theorem-proof is used to show the structural features of the theory (model) to establish it is sound and complete. After establishing that the theory is sound and complete, the next step is to provide the instantiation of the theory. This is achieved by mapping the core components of the theory to their corresponding instances. Additionally, a formal graphical tool termed as point graph (PG) is used to visualise the cases of the proposed axiomatic system. PG facilitates in modelling, and scheduling patient flows and enables analysing existing models for possible inaccuracies and inconsistencies supported by a reasoning mechanism based on PITL. Following that, a transformation is developed to map the core modelling components of the standards into the extended PG (PG*) based on the semantics presented by the axiomatic system. A real-life case (from the King’s College hospital accident and emergency (A&E) department’s trauma patient pathway) is considered to validate the framework. It is divided into three patient flows to depict the journey of a patient with significant trauma, arriving at A&E, undergoing a procedure and subsequently discharged. Their staff relied upon the UML-AD and BPMN to model the patient flows. An evaluation of their representation is presented to show the shortfalls of the modelling standards to model patient flows. The last step is to model these patient flows using the developed approach, which is supported by enhanced reasoning and scheduling