Methodology for automated Petri Net model generation to support Reliability Modelling

As the complexity of engineering systems and processes increases, determining their optimal performance also becomes increasingly complex. There are various reliability methods available to model performance but generating the models can become a significant task that is cumbersome, error-prone and tedious. Hence, over the years, work has been undertaken into automatically generating reliability models in order to detect the most critical components and design errors at an early stage, supporting alternative designs. Earlier work lacks full automation resulting in semi-automated methods since they require user intervention to import system information to the algorithm, focus on specific domains and cannot accurately model systems or processes with control loops and dynamic features. This thesis develops a novel method that can generate reliability models for complex systems and processes, based on Petri Net models. The process has been fully automated with software developed that extracts the information required for the model from a topology diagram that describes the system or process considered and generates the corresponding mathematical and graphical representations of the Petri Net model. Such topology diagrams are used in industrial sectors, ranging from aerospace and automotive engineering to finance, defence, government, entertainment and telecommunications. Complex real-life scenarios are studied to demonstrate the application of the proposed method, followed by the verification, validation and simulation of the developed Petri Net models. Thus, the proposed method is seen to be a powerful tool to automatically obtain the PN modelling formalism from a topology diagram, commonly used in industry, by: - Handling and efficiently modelling systems and processes with a large number of components and activities respectively, dependent events and control loops. - Providing generic domain applicability. - Providing software independence by generating models readily understandable by the user without requiring further manipulation by any industrial software. Finally, the method documented in this thesis enables engineers to conduct reliability and performance analysis in a timely manner that ensures the results feed into the design process

Petri Net Modelling for Enhanced IT Asset Recycling Solutions

From preliminary design through product sustainment to end of life removal, optimal performance through the entire life cycle, is one of the most important design considerations in engineering systems. There are a number of mathematical modelling techniques available to determine the performance of any system, or process, design. This paper focuses on the Petri Net technique for the representation and simulation of complex cases with the ultimate aim of automatically generating a model from the system, or process, description. If the model can be automatically generated changes can be investigated easily, enabling different designs to be investigated. Within this research, a Petri Net model is developed for a process of recycling IT assets. This model is simulated and programmed in Matlab©. The model enables the simulation of various flow paths through the recycling process, giving an understanding of the current process limiting factors. These can then be used to identify possible ways of improving the efficiency of the recycling process and enhancing the current IT asset management strategy. The future aim of this research is the automatic generation of a system model for complex industrial systems and processes by converting the SysML – based specifications into Petri Nets

Automated generation of a Petri net model: application to an end of life manufacturing process

As the complexity of engineering systems and processes increases, determining their optimal performance also becomes increasingly complex. There are various reliability techniques available to model performance, for example fault trees, simulation etc., but generating the models can become a significant task that is cumbersome, error-prone and tedious. This can result in significant resources being devoted to the generation of the models and there is much room for error. Hence over the years work has been undertaken into automatically generating reliability models. Such an approach enables the detection of the most critical components and design errors at an early design stage, supporting alternative designs and systems. The aim of the research described in this paper is the automatic generation of a Petri Net model for a given system or process. The Petri Net approach enables complex systems and processes to be modelled using a modular approach. The methodology of the automated Petri Net generation outlined in this work is to extract the information required for the model from the system description in a form used by industry, such as a UML Activity Diagram, into a database using XML transformations. An algorithm is then applied to generate the Petri Net incidence matrices of the necessary nets, which is the mathematical representation of the model. The algorithm builds the nets up in a modular fashion enabling changes to be made to the overall net in a cost effective way hence allowing various designs to be easily assessed. In this work the procedure will be demonstrated by its application to an end of life manufacturing process

A new methodology for automated Petri Net generation: Method application

A new methodology for automated Petri Net generation: Method applicatio

A multi-objective approach for resilience-based system design optimisation of complex manufacturing systems

Disruptive events in complex manufacturing systems (CMS), characterised by labour-intensive processes and repetitive activities, render these systems vulnerable. In order to tackle this challenge, an approach for resilience-based system design optimisation is proposed. The approach: (i) introduces a dynamic multi-dimensional resilience metric; and (ii) formulates the resilience as a multi-objective optimisation problem to improve CMSs resilience by finding an optimal human resource allocation model, considering design factors including redundancy, resources capacity and roles. The case study, selected to test the validity of the presented approach, show improvement in resilience and efficiency, in terms of throughput, resources utilisation and restoration time

Digital twin-enabled automated anomaly detection and bottleneck identification in complex manufacturing systems using a multi-agent approach

Digital twin (DT) models are increasingly being used to improve the performance of complex manufacturing systems. In this context, DTs automatically enabling anomaly detection, such as increase in orders, and bottleneck identification, such as shortage of products, can significantly enhance decision-making to mitigate the consequences of the identified bottlenecks. The existing literature has mainly focused on implementing top-down approaches for analysing the bottlenecks without considering the emergent behaviour of micro-level agents, including inventory levels and human resources, and their impact on the macro-level system’s performance. In order to handle the aforementioned challenges, this paper extends the current literature by proposing a novel DT integrated in a multi-agent cyber physical system (CPS) for detecting anomalies in sensor data, while identifying and removing bottlenecks that emerge during the operation of complex manufacturing systems. An extended 5 C CPS architecture, using multi-agent approach, is implemented to allow DT integration. The agent-based simulation technique enables capturing the probabilistic variability, and aggregate parallelism and dynamism of parallel dynamic interactions within the DT-CPS. A new single agent at the exo-level of the multi-level agent-based modelling structure, called the ‘monitoring agent’, is introduced in this research. The agent detects anomalies and identify bottlenecks through communicating with other agents in different levels automatically. The DT-CPS provides feedback automatically to the physical space to remove and mitigate the identified bottlenecks. The proposed DT based multi-agent CPS has been tested successfully on a real case study in a cryogenic warehouse shop-floor from the cell and gene therapy industry. The performance of the studied cryogenic warehouse is continuously measured using real-time sensor data. The analyses of the results show that the proposed DT-CPS improves the utilisation rates of human resources, on average, by 30% supporting decision making and control in complex manufacturing systems.Innovate UK: 104515. Engineering and Physical Sciences Research Council (EPSRC): EP/R032718/

Digital twin integration in multi-agent cyber physical manufacturing systems

Complex manufacturing and supply chain systems consist of concurrent labour-intensive processes and procedures with repetitive time-consuming tasks and multiple quality checks. These features may pose challenges for the efficient operation and management, while manual tasks may significantly increase human errors or near misses, having impact on the propagation of effects and parallel interactions within these systems. In order to handle the aforementioned challenges, a digital twin (DT) integrated in a multi-agent cyber-physical manufacturing system (CPMS) with the help of RFID technology is proposed. The proposed reference architecture tends to improve the trackability and traceability of complex manufacturing processes. In this research work, the interactions occurring both within a single complex manufacturing system and between multiple sites within a supply chain are considered. For the implementation of the integrated DT-CPMS, a simulation model employing the agent-based modelling technique is developed. A case study from a cryogenic supply chain in the UK is also selected to show the application and validity of the proposed digital solution. The results prove that the DT-CPMS architecture can improve system’s performance in terms of human, equipment and space utilisations

RFID application in a multi-agent cyber physical manufacturing system

In manufacturing supply chains with labour-intensive operations and processes, individuals perform various types of manual tasks and quality checks. These operations and processes embrace engagement with various forms of paperwork, regulation obligations and external agreements between multiple stakeholders. Such manual activities can increase human error and near misses, which may ultimately lead to a lack of productivity and performance. In this paper, a multi-agent cyber-physical system (CPS) architecture with radio frequency identification (RFID) technology is presented to assist inter-layer interactions between different manufacturing phases on the shop floor and external interactions with other stakeholders within a supply chain. A dynamic simulation model in the AnyLogic software is developed to implement the CPS-RFID solution by using the agent-based technique. A case study from cryogenic warehousing in cell and gene therapy has been chosen to test the validity of the presented CPS-RFID architecture. The analyses of the simulation results show improvement in efficiency and productivity, in terms of resource time-in-syste

Design for Digitally Enabled Industrial Product-Services Systems

Planning the life cycle of industrial product-service systems (IPS2) is highly challenging due to uncertainties experienced in predicting supply (e.g. spares) and demand (e.g. availability) related factors. Whilst digitalisation offers numerous exciting avenues, industry is finding it challenging to realise the potential benefits. This paper focuses on how to design the set of digital technologies and methodologies that serve as enabling capabilities to optimise value across the life cycle. This involves offering a step by step process to compare alternative improvement opportunities (e.g. data modelling, digital twins) with the justification to support investment decisions. The systematic design methodology is tested on an aerospace component, demonstrating the added value of digitally enabled IPS2