Digital Toolkit for optimisation of operators and technology in manufacturing partnerships (DigiTOP)

在迈向“工业4.0”的过程中，制造业正经历着向数字化制造的重大转变。通过将新的数字制造技术(DMT)引入车间流程，制造过程的数字化和互联程度的提高将不可避免地给工人的角色和手工任务带来实质性的变化。与此同时，制造业劳动力本身也在发生变化--在全球和全国范围内--包括更古老、更具流动性、更具文化多样性和较少专业/技能的劳动力池。简单地假设工人将承担赋予他们的新角色可能是不够的；为了确保工人成功地接受新系统并确保新系统的运作表现，将用户需求纳入数字制造技术设计是很重要的。在过去，人的因素塑造了制造业中使用的工具，使人们安全，使工作更容易，并使劳动力更有效率。需要新的方法来捕获和预测这些新类型的技术(如机器人、快速演变的工作空间和数据驱动系统)所带来的变化的影响。这些方法包括用于捕获工作场所性能的嵌入式传感器技术、用于合成和分析这些数据的机器学习和数据分析，以及用于支持有关数字制造工作场所应如何运作的决策的新的可视化方法，可能是实时的。DigiTOP项目将开发所需的新的基本知识，以可靠和有效地捕获和预测数字制造工作场所的性能，整合人员和技术的行动和决策。它将通过数字工具包提供这些知识，该工具包将包括三个要素：i)数字制造性能捕获的传感器集成和数据分析规范i)对四个工业数字制造使用案例的影响进行量化分析；ii)在线交互工具(S)，以支持实施数字制造技术的制造决策数字TOP项目汇集了一个具有制造、人为因素、机器人和人机交互专业知识的团队，以开发新的方法来捕获和预测数字制造对未来工作的影响。该项目将与一系列行业合作伙伴密切合作，包括捷豹路虎、BAE系统公司、巴布科克国际公司和高价值制造弹射器，共同创建行业指定的用例进行检查。DigiTOP的总体目标是根据新的基础工程和科学知识制作一个工具包，使工业能够提高生产率，支持数字制造技术的采用，并通过考虑人的需求和能力来降低未来数字制造技术的实施风险。

The manufacturing industry, with the drive towards 'Industrie 4.0', is experiencing a significant shift towards Digital Manufacturing. This increased digitisation and interconnectivity of manufacturing processes is inevitably going to bring substantial change to worker roles and manual tasks by introducing new digital manufacturing technologies (DMT) to shop floor processes. At the same time, the manufacturing workforce is itself also changing - globally and nationally - comprising of an older, more mobile, more culturally diverse and less specialist / skilled labour pool.It may not be enough to simply assume that workers will adopt new roles bestowed upon them; to ensure successful worker acceptance and operational performance of a new system it is important to incorporate user requirements into Digital Manufacturing Technologies design. In the past, Human Factors has shaped the tools used in manufacturing, to make people safe, to make work easy, and to make the workforce more efficient. New approaches to capture and predict the impact of the changes that these new types of technologies, such as robotics, rapidly evolvable workspaces, and data-driven systems are required. These approaches consist of embedded sensor technologies for capture of workplace performance, machine learning and data analytics to synthesise and analyse these data, and new methods of visualisation to support decisions made, potentially in real-time, as to how digital manufacturing workplaces should function. The DigiTOP project will develop the new fundamental knowledge required to reliably and validly capture and predict the performance of a digital manufacturing workplace, integrating the actions and decision of people and technology. It will deliver this knowledge via a Digital Toolkit, which will have three elements: i) Specification of sensor integration and data analytics for performance capture in Digital Manufacturingii) Quantitative analysis of the impact of four industrial Digital Manufacturing use casesiii) Online interactive tool(s) to support manufacturing decision making for implementation of Digital Manufacturing TechnologiesThe DigiTOP project brings together a team with expertise in manufacturing, human factors, robotics and human computer interaction, to develop new methods to capture and predict the impact of Digital Manufacturing on future work. This project will work closely with a range of industry partners, including Jaguar Landrover, BAE Systems, Babcock International and the High Value Manufacturing Catapult to co-create industry-specified use cases to examine. The overall goal of DigiTOP is to produce a toolkit, derived from new fundamental engineering and science knowledge, that will enable industry to increase productivity, support Digital Manufacturing Technology adoption and de-risk the implementation of future Digital Manufacturing Technologies through the consideration of human requirements and capabilities.