Risk management decision-making models for human-centered 4.0/5.0 assembly/disassembly production

一个可持续发展的企业必须更加重视平衡，实际上是优化其绩效要求与员工的福祉。在可持续发展和无节制创新的背景下，我们的业务现实包括不确定性和不断的适应和调整。企业必须具有弹性，即在可预见的情况下保持稳健，在面对不确定性时保持敏捷。可用于操作和职业健康与安全（OHS）风险的优化和集成管理的模型是基于以下假设：所表示的业务系统的行为是可预测的，并且可以完全分解为其组成部分。这些模型还旨在将所有系统可变性限制在既定的边界内。为了理解真实工业条件下的商业管理系统并支持决策制定，用于表示系统功能的模型随着时间的推移向集成的系统性和前瞻性模型发展是至关重要的，这些模型允许组合不同的可变性和不确定性来源。因此，拟议研究活动的目的是开发以人为本、弹性和可持续的4.0/5.0组装/拆卸生产的尖端风险管理决策模型。我们将使用基于综合设计的混合方法（定性和定量），从航空部门和École de technology supemrieure的应用人为因素实验室的装配/拆卸试验台进行实际案例研究。首先，将进行人为因素/人体工程学研究，以整合适当的数据，以记录未来数字化工作的十二个现实案例研究。其次，我们将为案例研究和实验室测试设计联合工业工程(IE)-人体工程学/人为因素（HF/E）研究方案，每个案例研究将部署在应用人为因素实验室组装/拆卸试验台上。第三，我们将对12个现实案例进行实验室实验，以产生研究的原始数据和模型系统。最后，我们将使用安全、可靠和以人为中心的基于人工智能的算法以及专家启发来量化模型。该提案将提供尖端的决策模型和知识，以平衡和优化组织绩效要求与流程数字化道路上工人的福祉。加拿大的一个高度优先的工业部门，即航空，预计将取得科学进展。装配/拆卸是制造业的一项基本活动，除运输部门外，其他工业部门将通过环境化从这些发展中受益。

A sustainable business must place increased emphasis on balancing, indeed optimizing its performance imperatives with the wellbeing of its workers. In a context of sustainable development and unbridled innovation, the reality of our business includes uncertainty and constant adaptation and adjustments. Businesses must be resilient, that is, robust when conditions are foreseeable, and agile in the face of uncertainty. The models available for optimal and integrated management of operational and occupational health and safety (OHS) risks are based on the hypothesis that the business system represented behaves predictably and can be deconstructed entirely into its component parts. These models also aim to confine all system variability within established boundaries. To understand business management systems under real industrial conditions and support decision making, it is crucial that the models used to represent system functioning evolve over time towards integrated systemic and proactive models that allow combining diverse sources of variability and uncertainties. The aim of the proposed research activities is therefore to develop cutting-edge risks management decision-making models for human-centered, resilient and sustainable 4.0/5.0 assembly/disassembly production. We shall use a mixed approach (qualitative and quantitative) based on an integrated design, in realistic case studies drawn from the aeronautical sector and an assembly/disassembly test bench of the Applied Human Factors Lab of École de technologie supérieure. Firstly, a human factors/ergonomics study will be done to consolidate proper data to document twelve realistic case studies of future digitalized work. Secondly, we will design joint industrial engineering (IE)-ergonomics/human factors (HF/E) research protocols for the case studies and lab test each case study to be deployed on the Applied Human Factors lab assembly/disassembly test bench. Thirdly, we will conduct lab experiment for the twelve realistic case studies to produce original data and model systems studied. Finally, we will quantify the models using safe, trustworthy and human-centered artificial intelligence-based algorithms as well as expert elicitation. This proposal will provide cutting-edge decision-making models and knowledge to balance and optimize organizational performance imperatives with the wellbeing of workers on the path to processes digitalization. Scientific advances are expected for one high-priority industrial sector in Canada, namely aeronautics. Assembly/disassembly being an essential activity in manufacturing, among others in the transportation sector, other industrial sectors will benefit from these developments through contextualisation.