An ontology-based approach for integrating engineering workflows for industrial assembly automation systems

Modern manufacturing organisations face a number of external challenges as the customer-base is more varied, more knowledgeable, and has a broader range of requirements. This has given rise to paradigms such as mass customisation and product personalisation. Internally, businesses must manage multidisciplinary teams that must work together to achieve a common goal despite spanning multiple domains, organisations, and due to improved communication technologies, countries. The motivation for this research is to therefore understand firstly how the multiplicity of stakeholders come together to realise the ever increasing and ever more complex number of product variants that manufacturing systems must now realise. The lack of integration of engineering tools and methods is identified to be one of the barriers to smooth engineering workflows and thus one of the key challenges faced in the current dynamic market. To address this problem, this research builds upon previous works that propose domain ontologies for representing knowledge in a way that is both machine and human readable, facilitating interoperability between engineering software. In addition to this, the research develops a novel Skill model that brings the domain ontologies into a practical, implementable framework that complements existing industrial workflows. The focus of this thesis is the domain of industrial assembly automation systems due to the role this stage of manufacturing plays in realising product variety. Therefore, the proposed ontological models and framework are applied to product assembly scenarios. The key contributions of this work are the consolidation of domain ontologies with a Skill model within the context of assembly systems engineering, development of a broader framework for the ontologies to sit within that complements existing workflows. In addition, the research demonstrates how the framework can be applied to connect assembly process planning activities with machine control logic to identify and rectify inconsistencies as new products are introduced. In summary, the thesis identifies the shortcomings of existing ontological models within the context of manufacturing, develops new models to address those shortcoming, and develops new, useful ways for ontological models to be used to address industrial problems by integrating them with virtual engineering tools

Income and Inequality Outcomes of Arms Exports: Where Does the Marxist Argument Stand?

Although in 21th Century not a single country could be classified as a purely capitalist or socialist state, but history still remembers the old politico-economic block (Bi Polar) formation of some countries as the proponents of capitalistic economic system and some as the followers of socialism. It is thought that the reason behind two World Wars was no other than the effort to dominate one economic system over the other. The enmity between the proponents of each of these systems is still alive today and the allies of both the sides are claiming rivalry to each other, especially the main champions of the systems. After the world wars, both the groups have not only economically and politically maltreated each other in the era of cold war, but have also started a race of militarization and weaponization to protect themselves from the potential fears from each other. By presenting the situation regarding exports of arms as well as by portraying the situations of per capita income and income inequality for previously been socialist (China and Russia) and capitalist (US and UK) states, the current study intends to view these two blocks from the Marxist lens. The main question of research tried to answer in the current study encompasses the following sub-questions, whether or not the capitalist economies are: a) exhibiting a butter versus gun trade-off in terms of allocation of scarce resources, b) a cause of low per capita income, c) demonstrating equal distributing of income

A lightweight approach for human factor assessment in virtual assembly designs : an evaluation model for postural risk and metabolic workload

The assessment and optimisation of postural stress and physical fatigue can be challenging and is typically conducted only after the design of manual operations has been finalised. However early assessment of manual operations and identification of critical factors that are deemed outside of an appropriate envelope can avoid the time and costs often associated with re-designing machines and layout for operator work processes. This research presents a low cost software solution based on a simplified skeleton model that uses operator position and workload data extracted from a simulation model used for virtual manufacturing process planning. The developed approach aims to assess postural stress and physical fatigue scores of assembly operations, as they are being designed and simulated virtually. The model is based on the Automotive Assembly Worksheet and the Garg’s metabolic rate prediction model. The proposed research focuses on the integration of virtual process planning, ergonomic and metabolic analysis tools, and on automating human factor assessment to enable optimisation of assembly operations and workload capabilities at early design stage

The cyber-physical e-machine manufacturing system : virtual engineering for complete lifecycle support

Electric machines (e-machines) will form a fundamental part of the powertrain of the future. Automotive manufacturers are keen to develop emachine manufacturing and assembly knowledge in-house. An on-going project, which aims to deliver an e-machine pilot assembly line, is being supported by a set of virtual engineering tools developed by the Automation Systems Group at the University of Warwick. Although digital models are a useful design aid providing visualization and simulation, the opportunity being exploited in this research paper is to have a common model throughout the lifecycle of both the manufacturing system and the product. The vision is to have a digital twin that is consistent with the real system and not just used in the early design and deployment phases. This concept, commonly referred to as Cyber Physical Systems (CPS), is key to realizing efficient system reconfigurability to support alternative product volumes and mixes. These tools produce modular digital models that can be rapidly modified preventing the simulation, test, and modification processes forming a bottleneck to the development lifecycles. In addition, they add value at more mature phases when, for example, a high volume line based on the pilot is created as the same models can be reused and modified as required. This research paper therefore demonstrates how the application of the virtual engineering tools support the development of a CPS using an e-machine assembly station as a case study. The main contribution of the work is to further validate the CPS philosophy by extending the concept into practical applications in pilot production systems with prototype products

Design evaluation of automated manufacturing processes based on complexity of control logic

Complexity continues to be a challenge in manufacturing systems, resulting in ever-inflating costs, operational issues and increased lead times to product realisation. Assessing complexity realizes the reduction and management of complexity sources which contributes to lowering associated engineering costs and time, improves productivity and increases profitability. This paper proposes an approach for evaluating the design of automated manufacturing processes based on the structural complexity of the control logic. Six complexity indices are introduced and formulated: Coupling, Restrictiveness, Diameter, Branching, Centralization, and Uncertainty. An overall Logical Complexity Index (CL) which combines all of these indices is developed and demonstrated using a simple pick and place automation process. The results indicate that the proposed approach can help design automation logics with the least complexity and compare alternatives that meet the requirements during initial design stages

A model for complexity assessment in manual assembly operations through predetermined motion time systems

Manual assembly processes are favoured for supporting low volume production systems, high product variety, assembly operations that are difficult to automate and manufacturing in low-wage countries. However, manual operations can dramatically impact assembly cycle times, quality and cost when the complexity of the manual operation increases. This paper proposes a method for assessing the process complexity of manual assembly operations, using a representation of manual operations based on predetermined motion time systems. The purpose of this framework is to provide a tool that can be used practically to assess, and therefore control, the complexity of manual operations during their design

The use of a complexity model to facilitate in the selection of a fuel cell assembly sequence

Various tools and methods exists for arriving at an optimised assembly sequence with most using a soft computing approach. However, these methods have issues including susceptibly to early convergence and high computational time. The typical objectives for these methods are to minimise the number of assembly change directions, orientation changes or the number of tool changes. This research proposes an alternative approach whereby an assembly sequence is measured based on its complexity. The complexity value is generated using design for assembly metrics and coupled with considerations for product performance, component precedence and material handling challenges to arrive at a sequence solution which is likely to be closest to the optimum for cost and product quality. The case presented in this study is of the assembly of a single proton exchange membrane fuel cell. This research demonstrates a practical approach for determining assembly sequence using data and tools that are used and available in the wider industry. Further work includes automating the sequence generation process and extending the work by considering additional factors such as ergonomi

Hydrogen fuel cell pick and place assembly systems : heuristic evaluation of reconfigurability and suitability

Proton Exchange Membrane Fuel Cells (PEMFCs) offer numerous advantages over combustion technology but they remain economically uncompetitive except for in niche applications. A portion of this cost is attributed to a lack of assembly expertise and the associated risks. To solve this problem, this research investigates the assembly systems that do exist for this product and systematically decomposes them into their constituent components to evaluate reconfigurability and suitability to product. A novel method and set of criteria are used for evaluation taking inspiration from heuristic approaches for evaluating manufacturing system complexity. It is proposed that this can be used as a support tool at the design stage to meet the needs of the product while having the capability to accept potential design changes and variants for products beyond the case study presented in this work. It is hoped this work develops a new means to support in the design of reconfigurable systems and form the foundation for fuel cell assembly best practice, allowing this technology to reduce in cost and find its way into a commercial space

A framework for automatically realizing assembly sequence changes in a virtual manufacturing environment

Global market pressures and the rapid evolution of technologies and materials force manufacturers to constantly design, develop and produce new and varied products to maintain a competitive edge. Although virtual design and engineering tools have been key to supporting this fast rate of change, there remains a lack of seamless integration between and within tools across the domains of product, process, and resource design - especially to accommodate change. This research examines how changes to designs within these three domains can be captured and evaluated within a component based engineering tool (vueOne, developed by the Automation Systems Group at the University of Warwick). This paper describes how and where data within these tools can be mapped to quickly evaluate change (where typically a tedious process of data entry is required) decreasing lead times and cost and increasing productivity. The approach is tested on a sub-assembly of a hydrogen fuel cell, where an assembly system is modelled and changes are made to the sequence which is translated through to control logic. Although full implementation has not yet been realized, the concept has the potential to radically change the way changes are made and the approach can be extended to supporting other change types provided the appropriate rules and mapping

Proposing a holistic framework for the assessment and management of manufacturing complexity through data-centric and human-centric approaches

A multiplicity of factors including technological innovations, dynamic operating environments, and globalisation are all believed to contribute towards the ever-increasing complexity of manufacturing systems. Although complexity is necessary to meet functional needs, it is important to assess and monitor it to reduce life-cycle costs by simplifying designs and minimising failure modes. This research paper identifies and describes two key industrially relevant methods for assessing complexity, namely a data-centric approach using the information theoretic method and a human-centric approach based on surveys and questionnaires. The paper goes onto describe the benefits and shortcomings of each and contributes to the body of knowledge by proposing a holistic framework that combines both assessment methods