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

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，我们业务的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）风险的最佳跨学科和综合管理的模型是基于这样一个假设，即所代表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来源。因此，拟议的研究活动的目的是通过应用新的研究策略来提高对复杂社会技术建模的基础知识来应对这些科学挑战。****我们将使用基于综合设计的混合方法（定性和定量）。首先，将进行人为因素研究，以确定需要考虑的操作和职业健康安全风险。其次，采用弹性工程方法，构建模型原型并进行验证。模型将捕获可变性源，以及每个源如何影响模型的功能，以及如何影响操作风险和OHS风险之间的权衡。第三，构建风险层次网络。使用人工智能算法将确定影响最大的因素（操作和OHS）。最后，将上述三个步骤的结果进行比较，以确定对于所研究的两个案例，如何整合，平衡和优化操作和职业健康安全风险及其不确定性，从而加强对企业的建议。***本建议将提供改进的工具，以指导今天的决策者选择平衡和优化生产和职业健康安全的必要性的手段。在加拿大，自然资源和航空航天这两个高度优先的工业部门有望取得科学进展

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.**