Integrating occupational health and safety to operational risks in real life industrials environments: a mixed optimization approach

将职业健康和安全与现实工业环境中的运营风险相结合：混合优化方法

• 批准号: RGPIN-2016-04930
• 负责人: Nadeau, Sylvie
• 金额: $ 1.97万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=615389
• 关键词: Integrating; occupational; health; safety; operational

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 businesses includes uncertainty and constant adaptation and adjustment. Businesses must be resilient, that is, robust when conditions are foreseeable, and agile in the face of uncertainty. The models available for optimal interdisciplinary 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. The aim of the proposed research activities is therefore to meet these scientific challenges by applying a new research strategy to improve fundamental knowledge on complex socio-technical modeling. We shall use a mixed approach (qualitative and quantitative) based on an integrated design. Firstly, a human factors study will be done to identify the operational and OHS risks to consider. Secondly, using a resilience engineering method, a modeled prototype will be constructed then validated. Variability sources will be captured by the model, as well as how each source affects the models’ functions and impacts trade-offs between operational and OHS risks. Thirdly, risk hierarchy networks will be constructed. Using an artificial intelligence algorithm the most influencing factors (operational and OHS) will be identified. Finally, the results from the three steps above will be compared to identify, for the two cases under study, how operational and OHS risks, as well as their uncertainties, can be integrated, balanced and optimized, thus strengthening the recommendations made to businesses. This proposal will provide improved tools to guide today’s decision-makers in choosing the means to balance and optimize the imperatives of production and OHS. Scientific advances are expected for two high-priority industrial sectors in Canada, namely natural resources and aerospace.

可持续的业务必须越来越重视平衡，实际上可以通过工人的福祉来优化其绩效要求。在可持续发展和无限创新的背景下，我们业务的现实包括不确定性，不断适应和调整。企业必须具有弹性，也就是说，在可能的情况下，在不确定性时敏捷。 这些模型可用于运营和职业健康与安全（OHS）风险的最佳跨学科和综合管理，基于以下假设：业务系统所代表的行为可以预测，并且可以完全解构为其组成部分。这些模型还旨在将所有系统可变性限制在既定边界内。 为了了解实际的工业条件下的业务管理系统并支持决策，至关重要的是，用于代表系统功能进化的模型朝着综合的系统性和主动模型，从而结合潜水员的可变性来源。因此，拟议的研究活动的目的是通过采用新的研究策略来改善有关复杂社会技术建模的基本知识，以应对这些科学挑战。 我们将根据集成设计使用一种混合方法（定性和定量）。首先，将进行人为因素研究，以确定要考虑的操作和OHS风险。其次，使用弹性工程方法，将构建建模的原型，然后验证。可变性来源将由模型捕获，以及每个源如何影响模型的功能并影响操作和OHS风险之间的权衡。第三，将构建风险层次结构网络。使用人工智能算法，将确定最有影响力的因素（操作和OHS）。最后，将比较上述三个步骤的结果，以确定在研究的两个案例中，可以整合，平衡和优化的操作和OHS风险以及它们的不确定性，从而加强对企业提出的建议。 该提案将提供改进的工具，以指导当今的决策者选择平衡和优化生产和OHS的需求的手段。预计加拿大两个高优先级工业部门的科学进步，即自然资源和航空航天。