Process Safety Management Research Articles

Managing process safety during difficult economic times

AbstractA number of economic factors have collided recently: the step drop in the price of oil, uncertainty in the United States and global economies, and mixed signals from economic and political leaders of many countries. All of these conditions have placed companies, especially those affected by oil prices under difficult economic stress. Companies are taking radical actions to, reduce capital and operational spending and in general, reduce cost. These economic pressures can be onerous on all areas of a business, but especially on the production floor‐level operations. Cost‐cutting dicta come from the executive levels, demanding a significant reduction in operating expenses or capital expenditures even when production levels are stable or increasing. While all areas of a company feel the impacts, key process safety impacts are felt on the shop floor; by the exact people, process safety is meant to protect, the operators, maintenance personnel and their supervisors. During these times of extreme economic pressure, it is imperative that process safety systems are not allowed to lose effectiveness. This article is intended to serve as a reminder of some impacts of cost cutting and to present tools to combat the loss of process safety effectiveness.

Similarity matching of food safety incidents in China: Aspects of rapid emergency response and food safety

Because food safety risks are becoming increasingly complex, food regulators and public health professionals should improve their ability in food safety management process. This study used the Carrado food poisoning incident in China as a case study to assist related managers in food safety assurance. The indicator system was established by extracting the descriptive information about food safety incidents, including ex-ante and ex-post information. In total, 295 food safety incident cases based on the characteristic attributes since 2000 were collected to establish a case database. We applied the algorithms of information entropy and cosine similarity to build the similarity matching model, and determined the degree of similarity between historical cases and the target case using MATLAB. By referring to the experiences of similar historical cases and the food safety accident emergency response plan, the emergency response was made. After the attribute difference analysis between similar historical cases and the target case was performed, the root causes of the target case were found. Finally, preventive measures were suggested. These results may provide a reference for food regulators to make rapid emergency response in the food safety incident and avoid the recurrence of similar incidents.

Process safety management in China: Progress and performance over the last 10 years and future development

AbstractIn this work, 790 documents involving Process Safety Management (PSM) published from 1998 to 2018 are collected. These papers are classified and VOSviewer is employed to conduct keyword co‐occurrence analysis. Furthermore, this work discusses the current situation of Chinese PSM in terms of incidents, regulations, and rules involving PSM, and compares the development of PSM in China with that of other countries. Through a Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis, this work proposes tasks that are necessary to improve the effectiveness of Chinese PSM. The results show that the numbers of documents involving PSM in China have experienced enormous growth after 2010, and safety management has been the most prominent topic. In addition, severe chemical incidents triggered by similar causes tend to reoccur in China because of failures of PSM. Therefore, to improve the effectiveness of Chinese PSM, much work remains to be done, with the primary task being to ensure that comprehensive PSM programs are implemented effectively. To improve the effects of implementation, strengthened regulations and legal systems related to PSM are the most important measures to be taken. Additionally, China should learn from the experiences of other countries and should share its experiences with other emerging economies.

Feasibility Evaluation of Designated Quantities for Chemicals Requiring Preparation for Accidents in the Korean Chemical Accident Prevention System.

To prevent chemical accidents, the United States (US), the European Union (EU), and the Republic of Korea operate legal systems, such as risk management plans (RMP) and process safety management (PSM), to prevent chemical accidents inside and outside the workplace. The duty to implement chemical accident prevention systems and the criteria for being a target workplace are dependent on the designated quantities of chemicals handled. A chemical accident prevention system is obligatory for storage and handling of legally declared chemicals in the workplace. Benzene, toluene, xylene, methyl ethyl ketone, and ethyl acetate are all flammable materials that are commonly used as solvents in the chemical industry. These substances are grouped into flammable substances groups in the US and the EU, and are managed with the same designated quantities. However, in Korea, the designated quantities are: benzene, 10,000 kg; toluene, xylene, and methyl ethyl ketone, 200,000 kg; and ethyl acetate, 20,000 kg. In order to evaluate the validity of the chemical quantities, fire explosion scenarios during chemical accidents were modeled using two modeling programs, Areal Location of Hazardous Atmosphere (ALOHA) and Korea Off-Site Risk Assessment Supporting Tool (KORA) software, under the same conditions. Similar damage radii were found for the five flammable materials with both pool fires and vapor cloud explosions (VCE). Based on these damage radii, the designated quantities of five substances were calculated and included in the range (10,000 to 13,500 kg). The results show that current designated quantities underestimate chemical substances, and for the prevention of accidents and post-management after chemical accidents, it is necessary to manage flammable substances under one grouping.

Risk Management in the Process of Personnel Allocation to Jobs

Abstract The strategy should be designed in such a way as the risk management can operate not only as a system for avoiding losses, but also risk management should allow recognizing and making use of occasions and create new opportunities for the organization. Risk management includes both an evaluation (analytical and evaluation) undertaking as well as planning and control activities aimed at minimizing (reducing) risk or maintaining it at an acceptable level. Security management can in particular be reduced to the issue of risk management, because risk is a quantitative expression of the functioning of systems in an environment where there are active sources of threats to system security. The article presents the problem of personnel allocation in hazardous conditions, emphasizing the possibilities of undertaking optimization actions in the safety management process. A mathematical model was formulated for this issue. An algorithm solving the problem of personnel allocation is presented. The proposed analysis is the starting point for determining the risk when using multi-station work.

Система управления технологической безопасностью на основе предсказывающих импульсных риск-моделей

Система управления технологической безопасностью на основе предсказывающих импульсных риск-моделей

Roadway Safety Management in Small Municipalities

Roadway safety management consists of network screening, diagnosis, countermeasure selection, economic appraisal, prioritization, and safety effectiveness. Application of the safety management process is limited in small municipalities because of data, statistical expertise, and resources required. This paper addresses the challenges faced by small jurisdictions and illustrates the implementation of the safety management process for local agencies in the Madison metropolitan area in Wisconsin. Jurisdiction-specific crash prediction models were developed by intersection type using data from over 4,000 intersections. Performance measures included the Equivalent Property Damage Only (EPDO) average crash frequency with Empirical Bayes adjustments and the Level of Service of Safety (LOSS). Wisconsin Crash Outcome Data Evaluation System (CODES) data was used to estimate local crash costs by severity and type. Sites were provisionally ranked in network screening, and diagnosis was automated based on intersection-observed crash types and distributions. Potential treatments were selected for each intersection and costs of treatments were obtained from local estimates and available literature. Crash cost benefit and treatment cost were used to estimate benefit–cost ratio (B/C) by site. A combination of sites that had the greatest overall cost-effective safety benefit on the network were selected through an incremental optimization process. This paper contributes to existing practice by illustrating the development of jurisdiction-specific crash prediction models, integration of pedestrian and cyclist crashes, application of EPDO and LOSS performance measures, and selection of sites with promise through an incremental optimization process for a given budget and resources available at the local level.

Construction method and application of real‐time monitoring and early‐warning model for anaerobic reactor leakage

AbstractThe anaerobic reactor is one of the most critical reaction devices for biogas engineering, wherein is usually a large amount of flammable gas methane. Fire and explosion accidents will be easily triggered if the gas leaks, threatening the surrounding buildings, equipment, personnel, and so forth. Avoiding the significant accidents caused by CH4 leakage has become a critical issue in the design and condition monitoring for an anaerobic reactor. This article presents a model construction method for leakage early‐warning. Incident database and hazard and operability analysis (HAZOP) can be utilized to identify the leakage risks, and computational fluid dynamics (CFD) simulation and consequence quantity calculation can be used to determine the consequence influence ranges. The calculation results can be employed to establish prediction models for abnormal situations. Process safety management (PSM) data and risk analysis results can be combined with the possible abnormal situations to assist operators in adopting the right solutions. An early‐warning system has been developed to illustrate the industrial application of the model. It can be concluded that collecting multi‐parameter values according to the real‐time changes in the actual production process, continuous monitoring and early‐warning of leakage risk, and so forth, will contribute to accident avoiding and emergency response in reactor operations.

An explorative context-aware machine learning approach to reducing human fatigue risk of traffic control operators

Traffic control operators are usually confronted with a high potential of human fatigue. Existing strategies to manage human fatigue in transportation are primarily by undertaking prescriptive “hours-of-work” regulations. However, these regulations lack certain flexibility and fail to consider dynamic fatigue-inducing factors in the context. To fill this gap, this study makes an explorative first step towards an improved approach for managing human fatigue. First, a fatigue causal network that can adequately represent the context factors and their dynamic interactions of human fatigue is proposed. Moreover, to overcome its problem of high dimension sparse matrix, a novel method based on the artificial immune system and extreme gradient boosting algorithm is introduced. A case study of vessel traffic management showed that the model could predict the fatigue level with high accuracy of 89%. Furthermore, to lower the risk of fatigue occurrence, a novel scheduling algorithm is also provided to adaptively arrange work for operators considering individual differences and work types. The study results showed that 27% of operators could be rearranged to reduce the possibility of human fatigue. Nevertheless, considering that more than half of operator were still fatigue in the case study, human fatigue is still a critical problem. It is hoped this research, as an explorative study, can offer insightful references to traffic management authorities in their safety management process with better operation experience.

Ranking of process safety cultures for risk-based inspections using indicative safety culture assessments

Although major hazard industries have no legal obligations to demonstrate a good safety culture, it is an increasingly important factor for risk-based inspections. This paper describes the development and evaluation of a relatively simple method for external indicative assessment of the process safety culture in major hazard industries. As a first step, a tool was developed. Second, the tool was successfully tested in a workshop with major hazard inspectors. After this ‘proof of concept’ and a few adaptations to improve the tool, quantitative evaluation and validation were carried out with a representative sample of major hazard inspectors in the Netherlands. In this stage, the tool comprised 30 questions, of which 19 sufficiently frequent valid responses were given for the validity test. The evaluations demonstrate that without specific preparations, inspection teams can use the tool to discriminate between plants with poor or good safety cultures. That is sufficient for ranking as additional input for risk-based inspection strategies. The resulting indicative ‘scores’ for safety culture correlate meaningfully with the quality of process safety management systems and the number of (legal) non-compliances, which were identified by the inspection team at the same occasion. The use of the tool can be further improved by training inspectors, making minor adaptations of the inspection process, and broadening the scope of a few questions. It is expected that external assessments of safety culture will become increasingly important not only for inspectorates, but also for a range of other external stakeholders.

The Development of Safety Plan Using Work Breakdown Structure (WBS) for Building Information Modeling (BIM)-Based Building Structure Work

One of the most influential factors on the project success in the construction industry is the safety management system. The rate of the occupational accidents in the construction sector is still very high according to the report of the Institution of Social Security Employment in Indonesia. One of the causes of the high rate of the occupational accidents that occur is due to the unnoticed work activities which is caused by the lack of control on the risks of the work activities. To discovered all of the activities on a work package, we can use a tool called WBS or Work Breakdown Structure. Besides that, by using the advancement of technology, it is expected to be used to improve safety performance on the construction projects effectively and efficiently. One of the advancements of technology which is already been used in the construction sector on this era is the BIM (Building Information Modeling). With using the BIM system on the construction projects, the quality of the work during the planning and construction phase will be increasing. Therefore, the development of a safety plan using WBS for BIM-based building structure work will be carried out in this study. The research method in this paper is a qualitative method and a case study will be presented on this paper to find out the effectiveness with using BIM in the safety management process. The results of this research are the occupational accident risks that are dominantly using the WBS and the development of the safety plan using WBS for BIM-based building structures work. The case study results the integrating of safety building information with the 4D model is very effective and efficient method to use on the safety management process. With the BIM system in the safety management process, the budget and the duration for safety inspection can be reduced because the hazardous of the occupational accidents can be identified faster according to the construction schedule. This research is expected to create a safety management strategy and can improve the safety performance on building construction projects in Indonesia.

A new unsupervised data mining method based on the stacked autoencoder for chemical process fault diagnosis

Process monitoring plays an important role in chemical process safety management, and fault diagnosis is a vital step of process monitoring. Among fault diagnosis researches, supervised ones are inappropriate for industrial applications due to the lack of labeled historical data in real situations. Thereby, unsupervised methods which are capable of dealing with unlabeled data should be developed for fault diagnosis. In this work, a new unsupervised data mining method based on deep learning is proposed for isolating different conditions of chemical process, including normal operations and faults, and thus labeled database can be created efficiently for constructing fault diagnosis model. The proposed method mainly consists of three steps: feature extraction by the convolutional stacked autoencoder (SAE), feature visualization by the t-distributed stochastic neighbor embedding (t-SNE) algorithm, and clustering. The benchmark Tennessee Eastman process (TEP) and an industrial hydrocracking instance are utilized to illustrate the effectiveness of the proposed data mining method.

Integrating cybersecurity in hazard and risk analyses

As operational and information technologies converge to allow for remote and real-time access to plant operating data and control functions, the process industry could become increasingly susceptible to cyber-attacks. Traditional hazard and risk analysis methods appear inadequate to identify, prevent, and mitigate such attacks. This paper discusses the significance of incorporating cybersecurity vulnerability analysis not just as part of process hazard analysis (PHA), but also in terms of protecting the process control network and implementing adequate safeguards in general against cyber threats. A layer of protection analysis (LOPA) is adapted to evaluate potential weaknesses and ensure safeguards for critical applications would be resistant to cyber-attacks. Integrating cybersecurity into hazard and risk analyses as well as other elements of process safety management (PSM) is demonstrated with examples, making the plant more resilient against both traditional and cyber threats.

Quality assessment between calibrated highway safety manual safety performance functions and calibration functions for predicting crashes on freeway facilities

Abstract Crash prediction models are commonly used for network screening in highway safety management process, where potential impacts of highway safety treatments are quantified. The Highway Safety Manual (HSM) provides crash prediction models for various types of highway facilities that are often referred to as safety performance functions (SPFs). Freeway facility SPFs in the HSM were developed using data gathered from the states of California, Maine, and Washington. When applying these HSM-default SPFs to a local jurisdiction, the HSM recommends calibration of HSM-default SPFs or development of jurisdiction-specific SPFs to improve the accuracy of crash predictions. This study first calibrated the HSM-default freeway SPFs and for further accuracy and comparison purposes calibration functions were developed using Kansas freeway data. The performance of calibrated HSM-default SPFs was then compared with developed calibration functions concerning the accuracy in crash prediction. Freeway facility calibration dataset included 521 freeway segments, 351 entrance-related speed-change lanes, and 366 exit-related speed-change lanes. Cumulative residual plots and several other goodness-of-fit measures were used to assess the quality of calibrated HSM-default SPFs and calibration functions. Calibration functions fitted better compared to calibrated HSM-default SPFs for Kansas freeway data. The methodology used in this study could be beneficial and practiced to any jurisdiction. Calibration functions could be used as an alternative to jurisdiction-specific SPFs or a replacement for HSM-default SPFs, which are frequently used in comparing alternatives, in calculating economic benefits of project improvements, and in estimating economic effectiveness of crash reduction in highway safety-related decision making.

Analysis of severe industrial accidents caused by hazardous chemicals in South Korea from January 2008 to June 2018

Major accidents in the chemical process industries are relatively rare, but the resulting harm to workers, property loss, business interruption, and the environment are very serious. This study investigates chemical accidents that occurred between January 2008 and June 2018 in South Korea, and proposes ways to prevent similar accidents from occurring by analyzing the main causes of these accidents. Nine core concepts were drawn from the analyses comparing chemical accidents in South Korea: (1) current casualties by type of worker, (2) how the scale of the enterprise affects the disaster, (3) chemical accidents by type of occurrence, (4) analysis of ignition sources, (5) chemical accidents by CPI facilities, (6) human and technical error, (7) chemical accidents by work situation, (8) chemical accidents by non-compliance of process safety management (PSM) standards, and (9) chemical accidents by hazardous materials. Although there have been no recent occurrences of large chemical accidents since 2017 due to various factors, our results indicate that the past frequency of such accidents area serious concern in South Korea. Understanding the root causes of these accidents can help to prevent the recurrence of similar accidents and to strengthen preventative measures in chemical plants.

Toward HAZOP 4.0 Approach for Managing the Complexities of the Hazard and Operability of an Industrial Polymerization Reactor

Conventional HAZOP is a collaborative and multidisciplinary activity to identify the hazards associated to operability of the chemical processes. Then the consequences and required safeguards of each potential deviation or failure are assessed qualitatively one by one. It is performed with the assumption of "one failure at the time" for the process parameters. Furthermore, process complexities such as multiple failures, domino effects, time and amplitude dependent deviations etc. are avoided to keep the HAZOP brainstorming sessions systematic and effective. Therefore, the quality and outcomes of HAZOP study are relatively subjective and depend on the experience and competency of the HAZOP team. This simplified approach cannot fully cover the hazard identification and risk assessment of the complex processes such as polymerization. Furthermore, the incident investigations show that almost all major accidents have occurred due to multiple failures or domino effects. This paper aims at developing a practical methodology in the context of "Industry 4.0" and particularly illustrate how dynamic simulation liberates the HAZOP team from the simplification assumptions such as one failure at the time or neglecting the domino effects during the lifecycle of the complex processes. An industrial styrene bulk free radical polymerization process has been chosen as the case study to depict the applicability of the proposed method. In continuation of this research, the dynamic simulation integrated with Artificial Intelligence (AI) algorithms and Multivariable Process Monitoring (MPM) together with virtual collaboration tools will be invoked towards a more practical and effective HAZOP 4.0 platform. Such a platform can be the foundation of the further Process Safety Management (PSM) elements such as "Operating manuals", "Training and Competency management", "Condition monitoring and predictive maintenance", "Management of Change", "Pre-Start-up Safety Review", etc.

WOMEN'S SAFETY CULTURE IN CHILDBIRTH AND RELATED INSTITUTIONAL FACTORS

ABSTRACT Objective: to analyze the safety culture of women in childbirth and related institutional factors based on the perceptions of nursing and medical professionals. Methods: a mixed, sequential explanatory study, conducted with nursing technicians, nurses and physicians of the obstetric center of a public maternity hospital in the city of Rio de Janeiro. Data collection took place from May to July 2018. The Hospital Survey on Patient Safety Culture questionnaire and descriptive statistical treatment were applied. Then, 12 semistructured interviews and thematic content analysis were applied and, finally, this data set was integrated. Results: most of the dimensions of the safety culture are weakened, especially in the areas of institutional organization, and the team lacks knowledge about the actions of the Patient Safety Center in the institution, the uniformity of care is deficient and the number of personnel for care is limited. The safety management process and work organization need adaptations. Conclusion: the safety culture of women requires improvements in team training, skilled care, work organization, and commitment of local management to qualified and safe care in hospital births.

System analysis: the kemeny’s median as an optimization model of the preferences group system of air traffic controllers of the danger of the characteristic errors

The systems of advantages of aviation operators of the “front line” on the indicators and characteristics of their professional activities is one of the indicators demonstrating the influence of the human factor on decision-making, and, consequently, on the “attitude towards dangerous actions or conditions”, which, in its turn, is one of the components of the current ICAO safety paradigm. The preference system is understood as an ordered series of the specified indicators and characteristics from the most dangerous to the least dangerous, including errors that can be made by air traffic controllers. Group systems of advantages have a number of properties (peculiarities of the prevailing in a particular society — control shift — opinions on the perception of threats and hazards, the influence of the attitude of instructor personnel to threats and dangers and the technology to overcome them, statistics of aviation accidents and serious incidents in the area of responsibility, etc.) that are desirable to take into account in the safety management process and that are found by aggregating individual systems of benefits. This aggregation occurs using strategies for making group decisions, from which one should point to the strategy of summing and averaging ranks, which is riskier, but allows establishing the degree of consistency of opinions using the Kendall concordance coefficient. An important strategy is based on the classical Savage decision-making criteria, which has an optimization content and allows minimizing deviations in opinions regarding the dangers of mistakes of both the majority and the minority of the group members. The Kemeny’s median has a pronounced nonparametric optimization content, but it is almost never used in studies of the influence of the human factor on decision making in aviation systems. Individual systems of preferences of m=37 air traffic controllers on the spectrum of n=21 characteristic errors were constructed by them using the usual method of pairwise comparisons and normative establishment of a part of the total hazard. The use of the technology for detecting and filtering out marginal thoughts — individual systems of advantages, which significantly differ from the general group, made it possible to distinguish a subgroup mA=26 with a high level of intragroup consistency of opinions: the coefficient of concordance is W=0.7144 and is statistically significant at a high level of significance a=1%. Individual preference systems of members of the mА subgroup were used to implement the heuristic algorithm and construct the desired Kemeny’s median, which improves the consistent preference system and has an unusually high coincidence with the group advantage systems obtained using other group decision strategies: the average value of Spearman’s rank correlation coefficient in 7 times increased its minimum acceptable value.

Process system resilience: from risk management to business continuity and sustainability

In general, by competition, energy efficiency, reduced staff, etc. process safety and risk management challenges have increased with a heavier focus of public perception on risks globally. This has necessitated exploring tools for transition from the narrower to a broader approach with goals of business continuity and sustainability for risk management. The application of resilience engineering is being explored for considering the dynamics of socio-technical aspects. This paper presents the systems-based resilience approach for risk management in the process industry and provides a description of process system architecture, functional requirements, and life cycle stages. This paper introduces the process resilience analysis framework (PRAF) and its four aspects. As an example, the 2012 Chevron Richmond Refinery incident is reviewed, and relationship is established between resilience and sustainability. The conclusion is drawn that using PRAF strengthens the resilience capabilities of a process system to foster business continuity and sustainability.

A Hybrid Data Mining Method for Tunnel Engineering Based on Real-Time Monitoring Data From Tunnel Boring Machines

Tunnel engineering is one of the typical megaprojects given its long construction period, high construction costs and potential risks. Tunnel boring machines (TBMs) are widely used in tunnel engineering to improve work efficiency and safety. During the tunneling process, large amount of monitoring data has been recorded by TBMs to ensure construction safety. Analysis of the massive real-time monitoring data still lacks sufficiently effective methods and needs to be done manually in many cases, which brings potential dangers to construction safety. This paper proposes a hybrid data mining (DM) approach to process the real-time monitoring data from TBM automatically. Three different DM techniques are combined to improve mining process and support safety management process. In order to provide people with the experience required for on-site abnormal judgement, association rule algorithm is carried out to extract relationships among TBM parameters. To supplement the formation information required for construction decision-making process, a decision tree model is developed to classify formation data. Finally, the rate of penetration (ROP) is evaluated by neural network models to find abnormal data and give early warning. The proposed method was applied to a tunnel project in China and the application results verified that the method provided an accurate and efficient way to analyze real-time TBM monitoring data for safety management during TBM construction.