Key Performance Indicators for Inherent Safety: Application to the Hydrogen Supply Chain Alessandro Tugnoli, a Gabriele Landucci, b and Valerio Cozzani a a Dipartimento di Ingegneria Chimica, Mineraria e delle Tecnologie Ambientali, Alma Mater Studiorum—Universita ` di Bologna, Bologna 40131, Italy; a.tugnoli@unibo.it (for correspondence) b Dipartimento di Ingegneria Chimica, Chimica Industriale e Scienza dei Materiali, Universita ` di Pisa, Pisa 56126, Italy Published online 13 April 2009 in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/prs.10303 The practice of inherent safety in process develop- ment and design asks for reliable and systematic assessment tools. In the present study, a novel quanti- tative approach developed for the inherent safety assessment of process flow diagrams in early design stages is presented. The output of the approach is a metric that quantifies the inherent safety fingerprint of the process scheme by a set of key performance indicators. Physical parameters are used for the quantification of the hazard deriving from materials, process conditions and equipment characteristics. The assessment resorts to the identification and modeling of credible accident consequences on humans and equipment. The adoption of tangible parameters based on consequence modeling yields a clear and sound picture of the inherent safety performance of a design option. An example of application focused on some envisaged options of the hydrogen supply chain (production, distribution, and utilization) is presented. Ó 2009 American Institute of Chemical Engineers Process Saf Prog 28: 156–170, 2009 Keywords: hydrogen production; hydrogen storage; inherent safety; key performance indicators; risk analysis; supply chain. INTRODUCTION Current strategies for the improvement of the safety performance of the process industry require the implementation of the inherent safety concept [1– 3]. However the practice of inherent safety in process development and design is presently limited or non- systematic. The availability of reliable tools for inher- ent safety assessment is a key issue in this context [2]. The framework for the quantitative assessment of in- herent safety is defined by several previous studies [4–6]. The main issues needed for such assessment are well summarized in the literature [2,7,8]. Most of the previous efforts were dedicated to the develop- ment of methods that address the stage of process conceptual design [9–17]. Recently, Khan and Amyotte [18,19] and Tugnoli et al. [20,21] have extended the inherent safety assessment to detailed design and lay-out definition. However, when coming to the detail of existing methods, it may be easily observed that several of these procedures are mainly based on scoring techniques and/or may require sub- jective judgment in large extent. Embedded assump- tions (e.g. fixed relative weight of the scoring param- eters, assessment framework developed for specific field of application, information detail of the input data required, poor reproducibility when expert judg- ment is involved, etc.) may hinder application or gen- erate biases in the outcomes, especially when specific technologies are assessed [7,8]. In the present study, the existing framework for in- herent safety assessment was used to define a novel quantitative methodology for the inherent safety assessment of alternative industrial processes. The output of the approach is a metric which quantifies the inherent safety fingerprint of the process schemes by evaluation of the expected outcomes of the hazard present in the system. The metric is based on a set of key performance indicators (KPIs). The goal of every single KPI is to assesses a specific aspect of the over- all inherent safety fingerprint of the system. The anal- ysis is particularly suitable as a decision supporting tool to be applied in early process design. Physical parameters are used for a solid quantification of the hazard from materials, process conditions and Ó 2009 American Institute of Chemical Engineers 156 June 2009 Process Safety Progress (Vol.28, No.2)