EVOLVABLE ASSEMBLY SYSTEMS - TOWARDS OPEN, ADAPTABLE AND CONTEXT-AWARE EQUIPMENT AND SYSTEMS

汽车、航空航天、制药和医疗等行业的最终产品组装是英国等高劳动力成本地区的关键生产过程。为了应对当前的挑战，制造商需要将目前资本密集型的装配线转变为能够对外部和内部变化做出反应、能够自我修复、自我适应和重新配置的智能系统。这一需求取决于：(1)对生产系统快速升级和缩减规模的需求；(2)当前装配系统缺乏对破坏性事件和需求波动的自主反应的事实；(3)经济和社会驱动因素，走向“制造即服务”。因此，需要一种全新的方法来开发未来的组装系统，该系统能够以极短的安装时间不断发展，以响应产品要求和需求的变化，并利用新兴的新技术降低维护、系统重新配置和能力升级的成本。随着自动化水平和类型的变化，未来的装配系统还将需要人工操作员参与混合决策、监控和系统适应的不同类型。这项拟议的研究将一个多学科和多部门的合作伙伴关系结合在一起，利用诺丁汉大学的技能，以及代表关键高价值制造公司的行业及其代表机构在多学科变革研究方面的既定记录。研究方案的目标是确定和验证可演化装配系统的愿景和支持架构、理论模型、方法和算法，以此作为开放、适应性、背景感知和成本效益生产的新平台。该研究方案将在适应性和成本效益高的制造领域实现新的范式转变，打破传统方法，并基于复杂的集体适应性制造系统中的以下基础研究挑战的创新交织：产品-过程-系统进化；数据分析；知识建模；涌现工程；以及开放制造。这些从根本上来说是“集体”的支柱，为新的极其灵活和可演变的制造基础设施提供了新的见解，预计将对未来生产平台的自配置、自组织、自适应和演变提出新的见解。这些支柱将共同预示着一种改变游戏规则的战略，即行业应对和解决当前和未来与保留和扩大英国制造业务相关的重大社会挑战的能力。研究将最终通过交付可快速配置和优化的强大且合规的制造系统来实现压缩的产品生命周期，从而减少生产启动时间和计划切换。这将为新的、小型和独立的生产利益相关者带来更多机会，特别是那些参与实现产品、工艺和组装系统共同进化的利益相关者。我们构建基础架构的方法，使用模拟和真实世界的数据来测试和填充模型，并与行业利益攸关方密切合作，将确保可扩展和可适应的方法，这些方法将在不同的制造部门之间转移。

Assembly of final products in sectors such as automotive, aerospace, pharmaceutical and medical industries is a key production process in high labour cost areas such as the UK. To respond to the current challenges manufacturers need to transform current capital-intensive assembly lines into smart systems that can react to external and internal changes and can self-heal, self-adapt and reconfigure. This need is dictated by: (1) demand for rapid ramp-up and downscale of production systems; (2) the fact that current assembly systems lack autonomous responsiveness to disruptive events and demand fluctuations; (3) an economics and societal drive towards 'manufacturing as a service'. Consequently, there is a need for a radically new approach towards development of future assembly systems able to continuously evolve to respond to changes in product requirements and demand with extremely short set-up times combined with low cost of maintenance, system reconfiguration and capability upgrade with emerging new technologies. As the level and type of automation changes, future assembly systems will also require a different type of engagement of human operators in hybrid decision-making, monitoring and system adaptation. The proposed research brings together a multidisciplinary and multi-sector partnership drawing upon skills from across the University of Nottingham with an established track record in multi-disciplinary transformative research, and industries representing key high value manufacturing companies together with their representative bodies. The goal of the research programme is to define and validate the vision and support architecture, theoretical models, methods and algorithms for Evolvable Assembly Systems as a new platform for open, adaptable, context-aware and cost effective production. The research programme will deliver a new paradigm shift in adaptable and cost effective manufacture that breaks with traditional approaches and is predicated on an innovative intertwining of the following foundational research challenges in complex collective adaptive manufacturing systems: Product-Process-System Evolution; Data Analytics; Knowledge Modelling; Emergence Engineering; and Open Manufacturing. These fundamentally 'collective', pillars for a new extremely flexible and evolvable manufacturing infrastructure are expected to shed new insights on the self-configuration, self-organisation, self-adaptation and evolution of future production platforms. Together the pillars will presage a game-changing strategy for industry's ability to respond and solve current and future societal grand challenges linked to retaining and expanding manufacturing operations in the UK.The research will ultimately enable a compressed product life cycle through the delivery of robust and compliant manufacturing systems that can be rapidly configured and optimised, thus reducing production ramp-up times and programme switchovers. This will lead to increased opportunities for new, small and independent production stakeholders, particularly those involved in the realisation of product, process and assembly system co-evolution. Our approach of building an underlying architecture, using simulated and real-world data to test and populate models, and working closely with industry stakeholders, will ensure scalable and adaptable approaches that will be transferable between different manufacturing sectors.