Federico Zomparelli

Performance measurement for world-class manufacturing: a model for the Italian automotive industry

The continuous increase of competitiveness pushes each company to review its production processes in order to minimise as much as possible the costs and maximising customer service. The keywords are ‘zero waste’ and ‘zero loss’. There are a lot of different methods and techniques which are necessary to adopt to achieve these above objectives. Therefore, it is necessary to research the best way to implement optimisation principles. One of the best-known optimisation method is the world-class manufacturing (WCM). The implementation of WCM is a promising and a current topic. But, at the same time, it is a debated topic. The present study is a ‘pilot’ study that aims to investigate the applicability of WCM in an Italian small and medium enterprise that operates in the automotive sector. Therefore, the purpose of the research is twofold: Firstly, to provide a ‘model’ for determining the factors affecting the WCM based on core competencies of organisations. Secondly, to propose a ‘performance measures system’ in order to establish the relationship among critical factors. Hence, the research paper presents a blend of theoretical framework and practical applications. The final output is an appropriate performance measures to help managers in decision-making.

A Disaster Risk Management Performance Index to Assess Safety and Security in Industrial Plants

The goal of the research is to present an integrated approach that combines multi criteria analysis and disaster and emergency management. The study is based on a well know multi criteria technique, the Analytic Hierarchy Process (AHP). An AHP model is proposed in order to define a Disaster Risk Management Performance Index (DRMPI) that quantifies the performance and effectiveness of risk management to evaluate emergency alternative problems. This model is implemented in a real case study.

A Hybrid Probabilistic Model for Evaluating and Simulating Human Error in Industrial Emergency Conditions (HEIE)

Over the years, many techniques have been developed for human reliability analysis (HRA). The main weakness of traditional HRA approaches is the use of a simple classification scheme without a link to a model of cognition in terms of mental processes. The present work is an attempt in this direction through a particular hybrid probabilistic model. The human error in industrial emergency model aims to develop an integrated methodological approach useful in critical infrastructures during an emergency condition. The proposed method, starting from the integration of existing techniques, develops a very flexible tool, able to take into account the main external and internal factors responsible of human error in emergency conditions. The model is able to estimate the evolution of human behavior and error following the evolution of the emergency scenario. The final result is a simulation model that calculates the contextualized human error probability, through which it is possible to estimate a realistic and detailed scenario of the conditions during the emergency management.

Human factors challenges in disaster management scenario

The present chapter aims to propose a model to manage complexity during a disaster accident caused by human factors and errors. The model allows to evaluate the human error probability under critical conditions and stress conditions. A hybrid model based on Simulator for Human Error Probability Analysis (SHERPA) is proposed and analyzed. A specific area of application is investigated concerning the human behavior during an emergency situations in a petrochemical plant. Furthermore, the chapter proposes an innovative approaches for monitoring the human factors in industrial plant through KPIs indicators. The model is implemented in a real case study concerning a petrochemical company.

The Importance of Human Error and Reliability Management in Critical Conditions and Infrastructures

Protection and safeguarding of critical infrastructures (such us chemical industry, oil & gas industry, nuclear industry, etc.) is an important subject of study in the contemporary society. The study of risks associated to critical infrastructure required models of good practice to investigate the complexity of processes in case of accidents. The risk management can be viewed in two ways: human error and system reliability. In other words in terms of human error it is essential to ensure the operator performance to manage a complex system or an unexpected situation. While in terms of system reliability it is essential to ensure that a system is at least as reliable as the system it is replacing. The present chapter aims to analyze the main disasters occurred in critical infrastructures related to human errors or lack of reliability of systems.

Analysis of Reliability Aspects of Railway Accident Precursors: An Italian Case Study

The Railway transport system is experimenting a deep transformation nowadays. The continuous technological evolution and the raising the standard of living of the population have led today to an increase in the volume of rail traffic, both referred to the passenger and freight transport. Despite railways being a statistically safe form of transportation (due to guidance per rails, professional drivers, etc.) rail accidents may still happen. Safety in railway infrastructure must be understood as the safe performance of their functions by the main components. From this perspective it denotes a growing interest in the issue of safety in railway tunnels. In particular, the analysis of the structural aspects of reliability and maintenance goes to correlate safety analysis. The papers aims to ensure a proper level of safety in railway tunnels, through the adoption of measures of prevention and protection finalized at the reduction of critical situations. In the present study a rigorous methodological approach is proposed for a “typical” Italian railway tunnel.