A systematic literature review on intelligent automation: Aligning concepts from theory,practice, and future perspectives

With the recent developments in robotic process automation (RPA) and artificial intelligence (AI), academics and industrial practitioners are now pursuing robust and adaptive decision making (DM) in real-life engineering applications and automated business workflows and processes to accommodate context awareness, adaptation to environment and customisation. The emerging research via RPA, AI and soft computing offers sophisticated decision analysis methods, data-driven DM and scenario analysis with regard to the consideration of decision choices and provides benefits in numerous engineering applications. The emerging intelligent automation (IA) – the combination of RPA, AI and soft computing – can further transcend traditional DM to achieve unprecedented levels of operational efficiency, decision quality and system reliability. RPA allows an intelligent agent to eliminate operational errors and mimic manual routine decisions, including rule-based, well-structured and repetitive decisions involving enormous data, in a digital system, while AI has the cognitive capabilities to emulate the actions of human behaviour and process unstructured data via machine learning, natural language processing and image processing. Insights from IA drive new opportunities in providing automated DM processes, fault diagnosis, knowledge elicitation and solutions under complex decision environments with the presence of context-aware data, uncertainty and customer preferences. This sophisticated review attempts to deliver the relevant research directions and applications from the selected literature to the readers and address the key contributions of the selected literature, IA’s benefits, implementation considerations, challenges and potential IA applications to foster the relevant research development in the domain.     

A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network

This paper focuses on consensus reaching process (CRP) under social network in which the trust relationship expressed by linguistic information. A new feedback mechanism in social network group decision making (SN-GDM) is proposed, which mainly consists of the following two aspects: (1) The propagation of distributed linguistic trust is investigated to study trust relation among experts; (2) A maximum self-esteem degree based feedback mechanism is developed to produce personalized advice for reaching higher group consensus. To do so, a novel linguistic trust propagation method is proposed to obtain the complete trust relationship among group. The self-esteem degree is used to define the extent that an individual makes concessions. Then, a maximum self-esteem degree based optimal feedback mechanism is built to produce personalized advice to help inconsistent experts make change of their opinion. Its novelty lies in the establishment of an optimization model with the nonlinear group self-esteem degree function as the objective function while group consensus threshold as the restrictions. Therefore, the inconsistent experts will reach a group consensus with the minimum loss of self-esteem degree, and then, it achieves the optimal balance between individual self-esteem and group consensus. Finally, a ranking process is applied to derive the appropriate consensus solution.     

基于改进迭代最近点算法的接骨板贴合性快捷计算方法

为了快速计算出接骨板在断骨表面的最佳贴合位置,以减少手术中接骨板反复调整的次数,提出了一种基于改进迭代最近点（ICP）算法的接骨板贴合性快捷计算方法。首先,由医生指导在断骨表面选取贴合区域,并利用接骨板表面点的法向量之间的夹角提取接骨板的内曲面点云;然后,在对两组点云模型进行平滑处理并采用格点采样的方式来简化点云模型后,利用点云之间的特征关系进行初始配准;最后,对接骨板内曲面点云模型进行边界及内部特征关键点提取,并采用K-维树（KD-Tree）搜索邻近点,对接骨板的特征关键点和断骨表面选取区域执行ICP精确配准。以胫骨为例进行实验,实验结果表明,所提算法相较于近年所提配准算法在保持较高配准度的同时提高了配准效率,能够实现胫骨不同受损类型与接骨板之间的快速配准,并且对其他受损骨骼具有通用性。     

不完备系统多准则决策的云PDR方法

针对多准则决策问题的意义以及经典粗糙集方法在不完备系统方案排序问题中的不足,在前人基于概率优势关系(PDR)排序方法的基础上,结合云理论提出了基于云概率优势关系的不完备系统多准则决策方法,即云PDR排序法。将期望、熵、超熵等参数引入PDR方法,充分考虑了决策的模糊性、波动性和随机性,评价过程和结果更加客观全面。以煤炭资源型城市为例进行应用研究,获得其中各城市发展水平及其波动情况的排序,并通过与其他方法结果的比较验证了本文方法的优势与有效性。     

大截面板簧和稳定杆的热处理改进

合理选择淬火冷却介质和确定零件的材料产品质量取于受控状态和确保产品质量的提高。     

基于数值模拟的接水盘冲压成形工艺分析与设计

分析了冰箱接水盘的形状和结构特点 ,设计了零件的冲压成形工艺 ,运用板料成形有限元软件对其中的拉伸和翻边工艺进行数值模拟 ,得到成形过程中工件各部位的厚度分布和成形极限图 ,分析了在不同工艺条件下可能产生的缺陷及其原因 ,并确定其初始毛坯和中间毛坯的合理形状 ,有效地保证了成形工艺的可靠性     

中厚板在线30通道超声波探伤方法及应用

介绍了柳钢公司在生产锅炉板、压力容器板过程中，曾试用了６种探伤方法；而研制的３０通道在线超声波探伤法不仅可满足国家标准要求，而且能适应生产节奏，并具有快速、准确、简便的特点。     

中厚板轧机工作辊失效分析及对策

介绍了济钢中厚板厂使用国外高镍铬和高铬工作辊的主要失效形式 ,并对该工作辊的断裂和裂纹产生原因进行了分析 ,同时针对所存在的问题提出了对策和具体改进措施。     

混合室分配板成形工艺及模具设计

对混合室分配板零件介绍了一种落料拉伸成形和立体切沿分割的工艺思路以及模具结构和相关的理论计算 ,在实际应用中获得了好的效果。对同类形状产品 ,尤其是涉及到需要进行立体切沿分割的制件 ,可提供借鉴。     

Case‐based approach for supporting strategy decision making

The practice of strategy decision making proves that when the management board is strongly limited in its capacity to take rational actions, specifically in the context of great decision complexity and uncertainty, it is considered good practice to refer to experience through reasoning by analogy. In this paper, we would like to concentrate on supporting strategic decisions in small and medium enterprises (SMEs). The complexity of analogy‐based reasoning has its roots in an attempt to solve new problems based on past cases from a different domain, while we will focus on case‐based approach for a single domain. Additionally, we have chosen case‐based reasoning as a suitable decision‐making paradigm because it is corresponds to managers’ decision‐making behaviour. We present the STRATEGOS case‐based reasoning system for supporting strategic decision making by SMEs management boards and then the system evaluation by the dozens of chief executive officers (CEOs) from SMEs is presented. The results of the survey are promising and show the remarkable correspondence of the proposed solution with expectations and strategic behaviour of CEOs.