Environmental Audit improvements in industrial systems through FRAM

Environmental risk management requires specific methodologies to focus audit activities on the most critical elements of production systems. Limited resources require a clear motivation to put attention on specific technological, human, organizational components, and often should address the monitor of interactions among these elements. Recent research in environmental risk looks at methods to deal with complexity as interesting tools to reduce real impacts on pollution and consumption. In this paper, we provide evidence of the advantage in using the Functional Resonance Analysis Method (FRAM), not only to identify the criticalities of a complex production system but to provide a methodology to continuously improve the audit activities in parallel with the introduction of technique to reduce environmental risk. The case study presents the evolution of environmental audit in a sinter plant, proving the need for a review of the criticality list and the successful application of FRAM to refocus the control activities

Simulation model of the logistic distribution in a medical oxygen supply chain

Research activities on operations management in the last years are always more dedicated to supply chain and logistics optimization models. The study belongs to this branch and describes the problems related to a re-configuration of the distribution net in a company that produces medical oxygen cylinders for Italian market. The enterprise is particularly sensible to the optimization of supplying processes due to the characteristics of its product, as any delay in the delivery could create dangerous health situation for patients. The work has the objective to realize a software for supply chain management that could be a decision support system, analyzing strategic impacts that changes in distribution system create. In details, the model shows the differences in service level in case of closing one or more factories and the relative necessary changes in logistics net. The paper is articulated in the following parts: • analysis of company and construction of simulation model; • study of classic operation research techniques to solve dynamic vehicle routing problems; • description of possible scenes derived by strategic decision in closing factories; analysis of experiments and global conclusions and developments

Managing the bullwhip effect in multi-echelon supply chains

This editorial article presents the bullwhip effect which is one of the major problems faced by supply chain management. The bullwhip effect represents the demand variability amplification as demand information travels upstream in the supply chain. The bullwhip effect research has been attempting to prove its existence, identify its causes, quantify its magnitude and propose mitigation and avoidance solutions. Previous research has relied on different modeling approaches to quantify the bullwhip effect and to investigate the proposed mitigation/avoidance solutions. Extensive research has shown that smoothing replenishment rules and collaboration in supply chain are the most powerful approaches to counteract the bullwhip effect. The objective of this article is to highlight the bullwhip effect avoidance approaches with providing some interesting directions for future research

FRAM for systemic accident analysis: a matrix representation of functional resonance

Due to the inherent complexity of nowadays Air Traffic Management (ATM) system, standard methods looking at an event as a linear sequence of failures might become inappropriate. For this purpose, adopting a systemic perspective, the Functional Resonance Analysis Method (FRAM) originally developed by Hollnagel, helps identifying non-linear combinations of events and interrelationships. This paper aims to enhance the strength of FRAM-based accident analyses, discussing the Resilience Analysis Matrix (RAM), a user-friendly tool that supports the analyst during the analysis, in order to reduce the complexity of representation of FRAM. The RAM offers a two dimensional representation which highlights systematically connections among couplings, and thus even highly connected group of couplings. As an illustrative case study, this paper develops a systemic accident analysis for the runway incursion happened in February 1991 at LAX airport, involving SkyWest Flight 5569 and USAir Flight 1493. FRAM confirms itself a powerful method to characterize the variability of the operational scenario, identifying the dynamic couplings with a critical role during the event and helping discussing the systemic effects of variability at different level of analysis

An analytic framework to assess organizational resilience

Background: Resilience Engineering is a paradigm for safety management that focuses on coping with complexity to achieve success, even considering several conflicting goals. Modern socio-technical systems have to be resilient to comply with the variability of everyday activities, the tight-coupled and underspecified nature of work and the nonlinear interactions among agents. At organizational level, resilience can be described as a combination of four cornerstones: monitoring, responding, learning and anticipating. Methods: Starting from these four categories, this paper aims at defining a semi-quantitative analytic framework to measure organizational resilience in complex socio-technical systems, combining the Resilience Analysis Grid (RAG) and the Analytic Hierarchy Process (AHP). Results: This paper presents an approach for defining resilience abilities of an organization, creating a structured domain-dependent framework to define a resilience profile at different levels of abstraction, to identify weaknesses and strengths of the system and thus potential actions to increase system’s adaptive capacity. An illustrative example in an anaesthesia department clarifies the outcomes of the approach. Conclusions: The outcome of the RAG, i.e. a weighted set of probing questions, can be used in different domains, as a support tool in a wider Safety-II oriented managerial action to bring safety management into the core business of the organization

Efficacy of modified atkins ketogenic diet in chronic cluster headache. An open-label, single-arm, clinical trial

Introduction: Drug-resistant cluster headache (CH) is still an open clinical challenge. Recently, our group observed the clinical efficacy of a ketogenic diet (KD), usually adopted to treat drug-resistant epilepsies, on migraine. Aim: Here, we aim to detect the effect of KD in a group of drug-resistant chronic CH (CCH) patients. Materials and methods: Eighteen drug-resistant CCH patients underwent a 12-week KD (Modified Atkins Diet, MAD), and the clinical response was evaluated in terms of response (>= 50% attack reduction). Results: Of the 18 CCH patients, 15 were considered responders to the diet (11 experienced a full resolution of headache, and 4 had a headache reduction of at least 50% in terms of mean monthly number of attacks during the diet). The mean monthly number of attacks for each patient at the baseline was 108.71 (SD = 81.71); at the end of the third month of diet, it was reduced to 31.44 (SD = 84.61). Conclusion: We observed for the first time that a 3-month ketogenesis ameliorates clinical features of CCH

Enterprise Risk Management to Drive Operations Performances

Global competition characterizes the market of the new millennium where uncertainty and volatility are the main elements affecting the decision making process of managers that need to determine scenarios, define strategies, plan interventions and investments, develop projects and execute operations. Risks have been always part of entrepreneurships but a growing attention to the issues related to Risk Management is nowadays spreading. Along with the financial scandals in the affairs of some major corporations, the high degree of dynamism and the evolutions of markets need organizations to rapidly adapt their business models to changes, whether economic, political, regulatory, technological or social. In particular, managerial trends of business disintegration,decentralization and outsourcing, pushed organizations towards practices of information sharing, coordination and partnership. The difficulties that generally arise during the implementation of these practices underline the impact that critical risk factors can have on corporate governance. Operations, at any level, are highly affected in their performance by uncertainty, reducing their efficiency and effectiveness while losing control on the evolution of the value chain. Studies on risk management have to be extended, involving not only internal processes of companies but considering also the relationship and the level of integration of supply chain partners. This can be viewed as a strategic issue of operations management to enable interventions of research, development and innovation. In a vulnerable economy, where the attention to quality and efficiency through cost reduction is a source of frequent perturbations, an eventual error in understanding the sensibility of the operations to continuous changes can seriously and irreparably compromise the capability of fitting customers’ requirements. While studies and standards on risk management for health and safety, environment or security of information defined a well-known and universally recognized state of the art, corporate and operational risk management already needs a systematic approach and a common view. The main contributions in these fields are the reference models issued by international bodies. Starting from the most advanced international experiences, in this chapter some principles are defined and developed in a framework that, depending on the maturity level of organizations, may help to adequately support their achievements and drive operations performance

A monte carlo evolution of the functional resonance analysis method (FRAM) to assess performance variability in complex systems

Modern trends of socio-technical systems analysis suggest the development of an integrated view on technological, human and organizational system components. The Air Traffic Management (ATM) system can be taken as an example of one of the most critical socio-technical system, deserving particular attention in managing operational risks and safety. In the ATM system environment, the traditional techniques of risk and safety assessment may become ineffective as they miss in identifying the interactions and couplings between the various functional aspects of the system itself: going over the technical analysis, it is necessary to consider the influences between human factors and organizational structure both in everyday work and in abnormal situations. One of the newly introduced methods for understanding these relations is the Functional Resonance Analysis Method (FRAM) which aims to define the couplings among functions in a dynamic way. This paper evolves the traditional FRAM, proposing an innovative semi-quantitative framework based on Monte Carlo simulation. Highlighting critical functions and critical links between functions, this contribution aims to facilitate the safety analysis, taking account of the system response to different operating conditions and different risk state. The paper presents a walk-through section with a general application to an ATM process

Project selection in project portfolio management: an artificial neural network model based on critical success factors

While a growing body of literature focuses in detecting and analyzing the main reasons affecting project success, the use of these results in project portfolio management is still under investigation. Project critical success factors (CSFs) can serve as the fundamental criteria to prevent possible causes of failures with an effective project selection process, taking into account company strategic objectives, project manager’s experience and the competitive environment. This research proposes an innovative methodology to help managers in assessing projects during the selection phase. The paper describes the design, development and testing stages of a decision support system to predict project performances. An artificial neural network (ANN), scalable to any set of CSFs, classifies the level of project’s riskiness by extracting the experience of project managers from a set of past successful and unsuccessful projects