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TOOLS USED TO IMPROVE OPERATIONAL SAFETY IN JOHNS MANVILLE GLASS PLANTS

机译:用于改善约翰斯·曼维尔玻璃工厂中操作安全性的工具

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Johns Manville (JM) has a long-standing core value of safety at its operations around the world. As focused as the company has been on ensuring a safe work environment for its people, in the mid-1990s the need to balance regulatory compliance, employee engagement, and risk elimination led to a 15-year effort to modernize safety processes. This change process resulted in a safety program delivering a sustainable step-change in improved safety performance. Ultimately, the changes resulted in the development and refinement of formalized safety tools and approaches proven effective at identifying risk, and enabling the company to modify designs and reduce the potential for incident occurrence. Three of the most effective tools in managing risk associated with glass manufacturing operations include Management of Change (MOC), Process Hazard Analysis (PHA), and Technical Inquiry (TI). The MOC process provides a structured approach to evaluating many dimensions of potential risk associated with critical processes prior to making a physical change. In cases where the results of an MOC analysis suggest significant risk, a variety of PHA tools were developed to identify and correct probable failure modes in order to arrive at an acceptable risk profile. In situations where desired outcomes are not achieved and significant safety incidents have occurred, the TI process is employed to maximize learning and minimize the potential for a repeat of a loss event by effectively identifying and correcting root causes.
机译:约翰斯·曼维尔(JM)在全球范围内的运营中具有长期的核心安全价值。由于公司一直致力于确保员工的安全工作环境,因此在1990年代中期,平衡法规遵从性,员工敬业度和消除风险的需求导致了为期15年的使安全流程现代化的努力。这种变更过程导致了一项安全计划,该计划为改进的安全性能提供了可持续的步骤变更。最终,这些变更导致开发和完善了正式的安全工具和方法,这些工具和方法被证明可以有效地识别风险,并使公司能够修改设计并减少发生事故的可能性。用于管理与玻璃制造操作相关的风险的三个最有效的工具包括变更管理(MOC),过程危害分析(PHA)和技术咨询(TI)。 MOC流程提供了一种结构化的方法,可以在进行物理更改之前评估与关键流程相关的许多潜在风险。如果MOC分析的结果表明存在重大风险,则开发了多种PHA工具来识别和纠正可能的故障模式,以便获得可接受的风险状况。在未达到预期结果且发生重大安全事件的情况下,TI过程可通过有效地识别和纠正根本原因来最大限度地学习,并使重复损失事件的可能性降到最低。

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