Global drivers, sustainable manufacturing and systems ergonomics

This paper briefly explores the expected impact of the ‘Global Drivers’ (such as population demographics, food security; energy security; community security and safety), and the role of sustainability engineering in mitigating the potential effects of these Global Drivers. The message of the paper is that sustainability requires a significant input from Ergonomics/Human Factors, but the profession needs some expansion in its thinking in order to make this contribution. Creating a future sustainable world in which people experience an acceptable way of life will not happen without a large input from manufacturing industry into all the Global Drivers, both in delivering products that meet sustainability criteria (such as durability, reliability, minimised material requirement and low energy consumption), and in developing sustainable processes to deliver products for sustainability (such as minimum waste, minimum emissions and low energy consumption). Appropriate changes are already being implemented in manufacturing industry, including new business models, new jobs and new skills. Considerable high-level planning around the world is in progress and is bringing about these changes; for example, there is the US ‘Advanced Manufacturing National Program’ (AMNP)’, the German ‘Industrie 4.0’ plan, the French plan ‘la nouvelle France industrielle’ and the UK Foresight publications on the ‘Future of Manufacturing’. All of these activities recognise the central part that humans will continue to play in the new manufacturing paradigms; however, they do not discuss many of the issues that systems ergonomics professionals acknowledge. This paper discusses a number of these issues, highlighting the need for some new thinking and knowledge capture by systems ergonomics professionals. Among these are ethical issues, job content and skills issues. Towards the end, there is a summary of knowledge extensions considered necessary in order that systems ergonomists can be fully effective in this new environment, together with suggestions for the means to acquire and disseminate the knowledge extensions

The identification of knowledge gaps in the technologies of cyber-physical systems with recommendations for closing these gaps

The paper reports some training, education, and operational findings from an EU Horizon 2020 project that included the production of technology road‐maps for the domain of cyber‐physical systems (CPS). The project reviewed Deliverables from 72 CPS projects, all within Framework Programme 7 and Horizon 2020, including 18 from the ARTEMIS and ECSEL subprograms. This analysis led to the production of a “Knowledge Map” containing 75 technologies identified within the 72 projects as nodes in this map, connected by interoperability links. Filtering this map for each node, in turn, has led, in combination with other parts of the project, to some 48 recommendations for future focus and funding of developments in these technologies to assist in the rapid adoption of CPS in all domains. While the focus has been limited to European Union research and innovation, it is believed that the recommendations are transferable to other regions of the world

Job design for manufacturing in an era of sustainability

The paper explores the changes that are likely to be necessary as the world moves to a more sustainable way of life. When these changes are added to the development of the Internet of Things, in which it is envisaged that devices with some level of embedded intelligence will communicate with each other, as will intelligent services, it appears that our current ways of conducting job design may be found wanting. The principles of socio-technical design will still apply; how these principles will necessarily be extended is the subject of this paper; how to include aspects of sustainability, the need to train for resilience, etc

An experimental investigation of human mismatches in machining.

Mismatches refer to incompatibilities, inappropriateness, unsuitabilities or inconsistencies in machine operators’ actions which, if not addressed, would lead to errors. A fuller understanding of the rate at which mismatches occur and their causes would allow human aspects to be given proper consideration alongside hardware and technological issues in the design of new working environments, machines and tasks. This research highlights these human aspects of machining by examining mismatches in relation to various human characteristics. The human task–mismatch matching method was developed and applied in manual turning operations using experimental and questionnaire techniques on groups of 16 skilled and 12 unskilled operators. The skilled subjects were drawn from local industry and university technical staff. Unskilled subjects were engineering students, all of whom had some familiarity with machining through periods of industrial placement. Statistically significant relationships were established between mismatches and many of the human characteristics studied (skill, age, work experience, self-confidence and trust) when considering all the subjects as a single group, but for skilled operators alone, the only significant relationship was between self-confidence and trust. As a general conclusion, it can be confirmed that studying operators in their own workplace provides invaluable information for the design and operation of future workplaces, but that the relationships between performance and human characteristics remain difficult to establish formally

Decision-making after the product-service shift and some implications for ergonomics

This paper introduces a Decision-Making System Framework developed during research in a UK (EPSRC) funded Grand Challenge, entitled ‘Knowledge and Information Management – through life’ (KIM). The development of the framework is outlined, along with a brief outline of the validation work.. The future use of the framework will be discussed, with reminders that the goal of this framework is not to provide the ‘right’ answer, which is improbable, if not impossible, to predict when dealing with such extended and complex system

Human mismatches and preferences for automation

The research reported in this paper is concerned with gaining a better understanding of human factors issues in machining and the automation of manufacturing tasks. Mismatches between operators' performance and the requirements of machining tasks were experimentally studied with respect to the relationships with various human characteristics, including skill, age, work experience, self-confidence and trust. Twelve hypotheses concerning interrelationships between these characteristics were evaluated and important relationships established. It is considered that this increased knowledge of the rate of mismatches and an understanding of the causes is essential for the successful design of new working environments, machines and tasks. Much of this change to the working environment is likely to involve some degree of automation of the operators' tasks and so a second and important aspect of the study was designed to establish the extent to which preferred levels of automation were related to the same human characteristics. Four further hypotheses relating preferred levels of automation to skill, age, work experience, self-confidence and trust were tested with results that, in some cases, were unexpected and in others contradict the findings of previous research. © 2000 Taylor & Francis Ltd

Modelling the human components of complex systems

Complex systems are specified, designed, built and tested by humans, all of whom are immersed in a cultural environment that colours their emotions, cognition, decisions and behaviours. This paper presents a brief overview of culture, its sources, its measurement and its effects on the performance of complex systems. This paper also describes a series of culture and personality modelling tools that the authors have developed for the purpose of assessing the match of individuals and teams to missions or tasks, based on their cultural backgrounds and/or personality traits

Working towards a holistic organisational systems model

This paper presents an integration effort combining a number of soft factors modelling tools and considers the potential impact of such an overall tool in a system of systems environment. The paper introduces the tools developed and how it is envisaged they will work together to provide a comprehensive, coherent output. It is suggested that a suite of interoperable tools of this form could aid the design and operation of organisational systems and ensure they are fit for purpose

A practical example of a software factory: building a custom application for analysing EU Cyber Physical System (CPS) projects using Open Source software components

This paper is a retrospective analysis describing the development of a custom tool to organise data snippets derived from a substantial body of information, and a summary of the insights that this means of analysis provided in a very short time scale. The creation of data driven visualisations are of particular interest as they uncovered more cross-domain aspects of Cyber-Physical Systems projects than expert opinion had anticipated. These findings will be discussed fully in a second paper. The focus here is the development of the "Vulture" data scavenging tool using Open Source software as system components to create a custom application to serve the data collection and analysis requirements of a REA (Rapid Evidence Assessment) work-package within an EU funded project, Road2CPS

PEAT- a tool to predict team performance in systems

The paper describes the development of a tool to predict the success of a team in executing a process. It is expected to be used by systems engineers in initial stages of systems design, when concepts are still fluid, including the structure of the team(s) who are expected to be operators within the system. Currently, the tool is undergoing verification and validation; to date, the tool predicts fairly well and shows promise