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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
Practical reference on systematic accident prevention, investigative techniques, and contributing factors, derived from analysis of real accidents
Accident Prevention and Investigation enables readers to reduce the number of accidents and casualties during experiments at universities by using new approaches based on scientific knowledge and data. Demonstrated through case studies illustrating successful implementation, the book explores alternate perspectives on mechanisms and contributing factors of accidents, derived from investigation of real accidents.
Readers will first learn how accidents occur and understand how to prevent them. Next, they will learn how to use the discussed methods to conduct systematic accident prevention at universities, including fieldwork activities at sea.
In this book, readers will find:
- Tools to understand how to apply different accident prevention methods depending on the logistics of an experiment
- Guidelines to investigate and analyze accidents and near-misses
- Information on accident theory, risk management, and safety management systems
- Specific challenges at universities and how to systematically incorporate accident investigation and prevention when faced with factors from multiple industry types
- Helpful checklists to aid readers in the practical application of accident reduction
This book is an essential reference for faculty, researchers, and advanced students seeking to reduce the number of accidents on campus and in university-affiliated field work. It is also an ideal textbook for courses using a systematic approach to safety.
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Veröffentlichungsjahr: 2025
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
List of Figures
List of Tables
Preface
About the Author
Acknowledgments
Chapter 1 Current State of Accidents at Universities
1.1 Introduction
1.2 Background
1.3 Modes and Effects of Human Error
1.4 Transition from Human Error to Human Factors
1.5 Development of the SHEL Model
1.6 Change in the Social System and the Shift from Criminal to Safety Investigations
1.7 Widespread Use of SMSs
1.8 Development of the Swiss Cheese Model
1.9 Characteristics of Universities and Other Academic Institutions and SMSs
1.10 Explosion Accidents in Universities
1.11 Consequences of Inexhaustive and Nonscientific Accident Investigation
1.12 Challenges in Preventing Accidents in Universities, etc.
1.13 Conclusion
References
Chapter 2 Mechanisms of Accident Occurrence
2.1 Introduction
2.2 Concept of Hazard and Accident
2.3 Effect of a Layer of Defense
2.4 Situation of Defenses in Depth and Accidents
2.5 Near Misses
2.6 Lessons Learned
2.7 Conclusion
References
Chapter 3 Accident Models
3.1 Introduction
3.2 Historical Background of Accident Models
3.3 Problems in Each Accident Model
3.4 Accident Models Applicable to Each Industry
3.5 Conclusion
References
Chapter 4 Risk Management and Safety Management Systems
4.1 Introduction
4.2 Differences Between Risk Assessment and Risk Management
4.3 Concept of the Risk Management Process
4.4 The Core of the Safety Management System
4.5 Organizational Structure and Authority
4.6 Conclusion
References
Chapter 5 Human Factors
5.1 Introduction
5.2 Background
5.3 Aims and Scope of Human Factors Investigations
5.4 SHEL Model Applicable to Accidents at Universities, etc.
5.5 Safety Culture
5.6 Conclusion
References
Chapter 6 Accident Investigation and Analysis
6.1 Introduction
6.2 Points to Be Considered When Conducting Accident Investigations at Universities, etc.
6.3 Accident Investigation at the Accident Site
6.4 Witnesses Interviewing
6.5 Assessing the Evidence
6.6 Analysis Process
6.7 Writing the Accident Investigation Report
6.8 Follow-up Actions After Issuing Reports
6.9 Conclusion
References
Chapter 7 Contributing Factors Found in Accidents
7.1 Introduction
7.2 Methods of Utilizing Accident Factors
7.3 Software/Procedures
7.4 Hardware/Equipment
7.5 Environment/Atmosphere
7.6 Operators/Researchers
7.7 Organizations/Universities
7.8 Conclusion
References
Chapter 8 Systematic Accident Prevention
8.1 Introduction
8.2 Education
8.3 Workplace Inspections and Internal Audits
8.4 Investigation of Near Misses and Accidents
8.5 Follow-up Action
8.6 Using the Data
8.7 Conclusion
References
Abbreviations
Index
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1 Showerheads and their handles as a sample of slips. The left-hand handle is en...
Figure 1.2 A bathroom tap that can prevent slips. The tap in the left photograph is enlar...
Figure 1.3 The mechanism of the Tenerife tragedy. At the time, KLM’s SMS and crew ...
Figure 1.4 Safety management systems.
Chapter 2
Figure 2.1 Concept of hazard and accident (Fukuoka 2019).
Figure 2.2 Tank hatches on chemical tanker.
Figure 2.3 Priority ranking in risk reduction methods.
Figure 2.4 Accident, incident, and near-miss model.
Figure 2.5 Gas mask and chemical cartridge.
Figure 2.6 Self-contained air breathing apparatus.
Figure 2.7 Rescue situation by Fire Department Rescue Team.
Chapter 3
Figure 3.1 Analysis of accidents at University A using the domino theory.
Figure 3.2 Analysis of accidents at University A using the HFACS.
Figure 3.3 Analysis of accidents at University A using the SHEL–Reason hybrid mode...
Figure 3.4 Analysis of accidents at University A using the ATSB model.
Figure 3.5 Analysis of accidents at University A using the RMQMP model.
Figure 3.6 Analysis of accidents at University A using AcciMap.
Figure 3.7 Accident models applicable to different industries.
Chapter 4
Figure 4.1 Relationship between accidents and incidents as a classification for accident ...
Chapter 5
Figure 5.1 Information process of Captain A in a collision case (Fukuoka 2019). Note: Thi...
Chapter 6
Figure 6.1 Concept of hazard and accident and accident-contributing factors.
Figure 6.2 Analysis of explosion accidents at University A using event and contributory f...
Chapter 8
Figure 8.1 Relationship between BCM and SMS. Note: BCM involves the recovery of operation...
Figure 8.2 Process for preventing recurrence of accidents using data. Source: Adapted fro...
List of Tables
Chapter 1
Table 1.1 Analysis of avalanche accidents on Mt. Niseko Annupuri.
Chapter 2
Table 2.1 The accident-contributing factors by reanalyzing two explosion accidents using...
Chapter 3
Table 3.1 Classification of accident models.
Table 3.2 Summary of accidents and causes at University A (Fukuoka and Furusho 2022).
Chapter 4
Table 4.1 Key differences between risk assessment and risk management processes.
Table 4.2 Severity scales.
Table 4.3 Frequency scales (1).
Table 4.4 Frequency scales (2).
Table 4.5 Risk matrix.
Chapter 5
Table 5.1 Table of SHEL elements compatible with accidents in universities, etc. and ass...
Chapter 8
Table 8.1 Risk management process sheet using the risk matrix (example).
Guide
Cover
Table of Contents
Title Page
Copyright
List of Figures
List of Tables
Preface
About the Author
Acknowledgments
Begin Reading
Abbreviations
Index
End User License Agreement
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Accident Prevention and Investigation
A Systematic Guide for Professionals, Educators, Researchers, and Students
Koji Fukuoka
BCP & BCM Consulting,
Tokyo, Japan
Copyright © 2025 by John Wiley & Sons, Inc. All rights reserved, including rights for text and data mining and training of artificial intelligence technologies or similar technologies.
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List of Figures
Figure 1.1 Showerheads and their handles as a sample of slips. The left-hand handle is enlarged in the photograph on the right. The handle is marked with a red label with a warning. The large disk-shaped shower head directly above the handle is fixed. To the right of the fixed shower head is the portable shower head. These photographs were taken by the author in the same hotel in December 2022, including Figure 1.2.
Figure 1.2 A bathroom tap that can prevent slips. The tap in the left photograph is enlarged in the right one. The blue and red markings indicate whether water or hot water is supplied.
Figure 1.3 The mechanism of the Tenerife tragedy. At the time, KLM’s SMS and crew risk management were not functioning and are shown as dashed lines. The accident trajectory is indicated by the red arrow.
Source:
Adapted from Fukuoka (2024).
Figure 1.4 Safety management systems.
Figure 2.1 Concept of hazard and accident (Fukuoka 2019).
Figure 2.2 Tank hatches on chemical tanker.
Note:
The photograph shows a tank hatch on a chemical tanker being opened by a crew member. The tank hatch is a cylindrical structure on the deck of the ship, under which it is connected to the cargo tank. When the tank hatch is closed, the harmful liquid in the cargo tank cannot come into contact with people. The tank hatch is normally closed while the ship is underway and during loading and unloading and opened when loading and unloading are complete and the cargo tanks are cleaned by crew members. The same ship was involved in the same kind of accidents in 2010 and 2012, which resulted in the loss of crew members.
Source:
Adapted from the Japan Transport Safety Board.
Figure 2.3 Priority ranking in risk reduction methods.
Note:
This figure is a modification of ISO/IEC Guide 51 to help researchers in chemical experiments and field research activity to understand the effects of risk reduction. Designers and manufacturers carry out risk reduction by following steps 1–3 in sequence. This reduces the initial risk to the risk remaining after design. Users of equipment, devices, etc. are then required to write procedures, provide education and training, and wear PPE before experiments. However, even after PPE is worn, the residual risk remains when focusing on the risks shown on the right-hand side of the figure.
Source:
Adapted from Fukuoka (2016).
Figure 2.4 Accident, incident, and near-miss model.
Note:
The red arrows show the trajectory of the accident, and the accident occurs by penetrating all the multiple layers of defense because SMS and risk management are not working. The dotted lines for SMS and risk management show that they are not working. It is assumed that a serious near miss is controlled by the multiple layers of third-party defense and the occurrence of a serious accident is avoided.
Source:
Adapted from Fukuoka (2024).
Figure 2.5 Gas mask and chemical cartridge.
Note:
The gas mask and chemical cartridge are the devices worn by the victims; the chemical cartridge must be fitted with the appropriate cartridge depending on the target chemical, as the construction of the chemical cartridge differs depending on the type of gas. When using the equipment, the instruction manual states that the equipment must be used at a gas concentration of less than 1% and an oxygen concentration of 18% or more.
Source:
Adapted from Japan Transport Safety Board.
Figure 2.6 Self-contained air breathing apparatus.
Note:
The breathing apparatus consists of a container and a facepiece that supplies compressed oxygen or air.
Source:
Adapted from Japan Transport Safety Board.
Figure 2.7 Rescue situation by Fire Department Rescue Team.
Note:
The rescue team reduced the risk by using forced ventilation and oxygen cylinders to rescue the foreman and two workers who had collapsed in an anaerobic state before going to the rescue. The two people standing on the copper sulfide concentrate in the cargo hold are the rescue team. Next to the rescue team members is a ladder that the foreman and the workers used to descend from the cargo hold entrance.
Source:
Adapted from Japan Transport Safety Board.
Figure 3.1 Analysis of accidents at University A using the domino theory.
Figure 3.2 Analysis of accidents at University A using the HFACS.
Figure 3.3 Analysis of accidents at University A using the SHEL–Reason hybrid model.
Figure 3.4 Analysis of accidents at University A using the ATSB model.
Figure 3.5 Analysis of accidents at University A using the RMQMP model.
Note:
The table showing contributing factors or latent conditions refers to Table 2.1 in Chapter 2. The locations of the holes in the layers of defense in the local workplace and organization and the accident-contributing factors that caused these holes, as determined by scientific and comprehensive accident investigations, are listed and visualized in the table.
Figure 3.6 Analysis of accidents at University A using AcciMap.
Note:
Red arrows indicate causal relationships. The dashed box represents accident factors for which no causal relationship can be found anywhere.
Figure 3.7 Accident models applicable to different industries.
Source:
Adapted from Fukuoka (2017).
Note:
The arrow from the third quadrant to the second quadrant indicates the direction of development of industrial systems and accident models. The orange color in the fourth quadrant indicates universities, where no applicable accident models were identified by 2022, but epidemiological accident models were found to be applicable (Fukuoka and Furusho 2022).
Figure 4.1 Relationship between accidents and incidents as a classification for accident investigation.
Note:
The four main categories of event types are based on the emphasis on prevention of recurrence and proactive accident prevention. The relationship between the number of events is shown in the form of a pyramid based on Heinrich’s law. To the right of the events are the type of report to be made and the person responsible for the investigation.
Figure 5.1 Information process of Captain A in a collision case (Fukuoka 2019).
Note:
This diagram shows the information process of Captain A in relation to the collision accident in the narrow channel using Endsley’s situational awareness diagram. The diagram shows the chronological sequence of events that led to the situation not developing as Captain A had originally envisaged.
Figure 6.1 Concept of hazard and accident and accident-contributing factors.
Source:
Adapted from Fukuoka (2019).
Note:
This figure contrasts Figure 2.1 “Concept of hazard and accident” with the terminology used in the “Event and Contributory Factors Charts,” the accident analysis tool adopted by the IMO.
Figure 6.2 Analysis of explosion accidents at University A using event and contributory factors charts.
Note:
The bottom layer of the diagram shows the occurrence of events in chronological order. The factors behind the occurrence of the Accident event and the Casualty event are represented hierarchically in the upper layers. The top layer represents the problems faced by external organizations in relation to this accident. Between the lowest and highest layers are the problems of the laboratory and the university.
Figure 8.1 Relationship between BCM and SMS.
Note:
BCM involves the recovery of operations based on a preestablished Business Continuity Plan (BCP) in the event of a natural disaster, pandemic, or other event that has a significant impact on the organization’s operations. SMS is solely a method of managing environmental, health, and safety events.
Figure 8.2 Process for preventing recurrence of accidents using data.
Source:
Adapted from Fukuoka (2019).
List of Tables
Table 1.1 Analysis of avalanche accidents on Mt. Niseko Annupuri.
Table 2.1 The accident-contributing factors by reanalyzing two explosion accidents using the RMQMP model (Fukuoka and Furusho 2022/Springer Nature/CC BY 4.0).
Table 3.1 Classification of accident models.
Table 3.2 Summary of accidents and causes at University A (Fukuoka and Furusho 2022).
Table 4.1 Key differences between risk assessment and risk management processes.
Table 4.2 Severity scales.
Table 4.3 Frequency scales (1).
Table 4.4 Frequency scales (2).
Table 4.5 Risk matrix.
Table 5.1 Table of SHEL elements compatible with accidents in universities, etc. and associated safety recommendations.
Table 8.1 Risk management process sheet using the risk matrix (example).
Preface
When I was engaged in accident investigation analysis and report writing for accidents that occurred in various parts of Japan as an accident investigator for the Japan Transport Safety Board (JTSB), I had the opportunity to study scientific accident investigation analysis methods, including practical skills, at Cranfield University in the United Kingdom. What I learned and acquired there were accident mechanisms and universal methods of accident investigation and analysis and so forth, and I recognized that accident investigation and analysis is a comprehensive science involving many disciplines, such as engineering, psychology, physiology, sociology, and management. After retiring from the JTSB, I worked as the Emergency Response Coordinator and Occupational Health and Safety Section (OHS) Manager at the Okinawa Institute of Science and Technology Graduate University (OIST) in Okinawa, Japan, where I was responsible for the environmental, health, and safety and the development and operation of business continuity management (BCM).
The university experience allowed me to learn about the different approaches to safety used in many other industries, such as the maritime and service industries that I had experienced. This reality was further supported by my experience in academic exchanges, scientific papers, and literature. After OIST, as a professor (later special professor) in the Crisis Management Office at Kyushu University, I was responsible for formulating and operating the BCM against natural disasters and major accidents, as well as engaging in laboratory safety research.
At the time, I had just read a scientific paper Nature Chemistry describing the many accidents in university chemistry laboratories that had resulted in the casualties of faculty members, researchers, postgraduate students, and undergraduates, and that there had been no paradigm shift in laboratory safety, which never left my mind.
Scientific accident investigation analysis was not recognized within the university, nor were opportunities provided for education and training. Consequently, scientific accident investigation remained unnoticed. To prevent accidents in universities and academic institutions, I believed it was necessary for faculty members, researchers, and staff in charge of environmental safety and health office to first recognize scientific accident investigation analysis methods and the techniques for preventing accidents utilizing data derived from these analyses. It was during this time that I received an e-mail from John Wiley & Sons, Inc to write a book on accident prevention in universities and academic institutions.
This book prioritizes a clear description of theories and approaches related to accident occurrence and prevention, utilizing numerous figures, tables, and real-case examples to enhance understanding throughout each chapter. The primary audience for this book includes occupational health and safety professionals, laboratory technicians, chemical specialists, faculty members, fieldwork specialists, and diving officers. Secondary audiences encompass advanced undergraduates, graduate students, and researchers. Those who wish to learn about the mechanisms of accidents and incidents within academic and research institutions, individuals seeking to establish multiple layers of defenses to prevent errors from directly leading to serious accidents during laboratory experiments or fieldwork research activities, and those who aspire to reduce the number of accidents and incidents will find this book valuable as a text on accident theory and accident prevention. The case studies presented are all based on real accidents and incidents, and readers can derive lessons from these examples to contribute to the safety of their respective universities or research institutions. Furthermore, the accumulation of accident and incident data using the risk management and quality management process (RMQMP) approach model and other accident models introduced in this book is believed to contribute to the development of next-generation safety assurance tools for professionals, researchers, and technicians.
As discussed in Chapters 1 and 6, accident investigation reports need to be made publicly available so that many faculty members, staff, and students around the world can learn lessons from accidents and prevent accidents before they happen. The methodology is described in detail in Chapter 1, Section 1.12, Challenges in Preventing Accidents in Universities, etc. Throughout this book, common nouns are used to describe universities, laboratories, faculty members, researchers, students, etc., without using university names, research names, or individual names.
From Chapters 2 to 7, this book systematically explains the mechanisms of accident occurrence, various theories of accident prevention, and methods of accident investigation analysis in a scientific manner. Chapter 1 discusses the historical background of accident investigation alongside the current status of accident investigations in academic institutions like universities, comparing them with those conducted in other industries, and discusses the challenges universities and academic institutions face. Chapter 2 discusses useful concepts for researchers to prevent accidents, including hazard and accident concepts, the hierarchy of control for risk reduction, layers of defense to prevent accidents, the difference between near misses and accidents, and examples of lessons learned and their applications from scientific accident investigation results. Chapter 3 addresses significant accident models necessary for understanding accident mechanisms, discussing the historical development of these models, the overview and challenges of each model, and models applicable to various industries including academic institutions. Chapter 4 covers the risk management process and the safety management system (SMS) necessary to prevent accidents and mitigate damages in universities and academic institutions settings. Chapter 5 discusses human factors necessary for understanding the underlying factors of accidents. Chapter 6 provides a detailed description of the accident investigation process targeting serious accidents such as fire, explosions, casualties, and near misses that could potentially lead to serious accidents. It includes the safety of accident investigation personnel at accident sites, preservation and collection of evidence, evaluation of evidence, analysis methods, and preparation of accident investigation reports. Chapter 7 analyzes accidents involving chemical substances in laboratories, accidents during explosive usage, accidents involving high-pressure gases, accidents caused by refrigerants, accidents involving laboratory equipment, diving accidents during fieldwork activities, river accidents, mountain accidents, etc., using the RMQMP model to explain the contributing factors of each accident. Chapter 8 explains approaches to applying the BCM and SMS to universities and academic institutions as a systematic accident prevention system involving the entire organization in response to natural disasters and accidents. It also discusses preventing the recurrence of serious accidents and proactively preventing accidents from occurring.
About the Author
Dr. Koji Fukuoka obtained his PhD (Maritime Science and Technology) from Kobe University. After serving as a Judicial Police Officer and Coast Guard Officer in the Japan Coast Guard, he worked as a Security Manager at the Mandarin Oriental, Tokyo, where he formulated business continuity management (BCM), conducted education and training and conducted workplace inspections, and was appointed as a member of the Crisis Management Committee for safety and occupational health, ensuring the safety and security of the hotel. At the Japan Transport Safety Board (JTSB) of the Ministry of Land, Infrastructure, Transport, and Tourism, he studied scientific accident investigation and analysis methods at Cranfield University in the United Kingdom, and as a Supervisory Regional Accident Investigator, he conducted numerous accident investigations and analyses and prepared accident investigation reports. At Okinawa Institute of Science and Technology Graduate University, as Emergency Response Coordinator and Occupational Health and Safety (OHS) Section Manager, he established and operated BCM and safety management system (SMS) and worked to improve safety through field research activities and workplace inspections of laboratories. In collaboration with the Provost, he established a Risk Management Committee, and as a member of the committee, he visualized and compiled the major risks of the entire university into a risk matrix, determined the priorities of risk measures as system risk management using scientific methods, and established a system for risk control by each department and laboratory. At Kyushu University, where he was a Professor and Special Professor in the Crisis Management Office, he conducted research on accident prevention, established BCM, provided education and training for faculty members and administrative staff, set up a system of BCM workplace inspections and internal audits, and transformed the organizational structure into a resilient one.
Dr. Fukuoka has been a researcher and practitioner in the fields of safety, accident prevention, and loss control in industry and academia. During his tenure at the JTSB, he served as a consultant of the International Maritime Organization (IMO) for the “National Training Course on Marine Casualty and Incident Investigation” in Manila, Philippines. He provided English-language training to government officials. Additionally, he was appointed as a Correspondence Group Analyst for III (IMO’s Subcommittee on Implementation of IMO Instruments), analyzing accident investigation reports published by various countries and submitting analysis reports to the IMO. Dr. Fukuoka’s notable publications include Safer Seas: Systematic Accident Prevention (CRC Press Taylor & Francis Group 2019) and the scientific article “A new approach for explosion accident prevention in chemical research laboratories at universities” (Scientific Reports 2022).
Dr. Fukuoka is currently President of Business Continuity Plan (BCP) and BCM Consulting, where he works as a consultant on BCM and SMS as well as accident prevention in Tokyo, Japan.
Acknowledgments
I am indebted to many people who helped and encouraged me to complete this book; without them, this book would not have been possible. Although I cannot name all of them, I would like to thank those people whose assistance was indispensable. President Peter Gruss and Provost Mary Collins for their support in establishing the SMS and the business continuity management (BCM) during my tenure at Okinawa Institute of Science and Technology Graduate University (OIST) and the staff of the Occupational Health and Safety (OHS) who worked with me through many challenges. Top management of Kyushu University for their support in the establishment and operation of the BCM and the work related to laboratory safety. Faculty members who supported my accident prevention activities at the universities: Associate Professor Yoshinori Okada at OIST, Associate Professor Kenichi Honjoh and Associate Professor Yoshiyuki Yamagata at Kyushu University, and Professor Masao Furusho. I must express my great appreciation to Professor Graham Braithwaite, Director of Transport Systems at Cranfield University, for teaching me scientific accident investigation and analysis methods at Cranfield University in the United Kingdom.
I would like to take this opportunity to thank the many members of the Asian Conference on Safety and Education in the Laboratory who provided opportunities for discussion, debate, and presentations on laboratory safety and related topics.
Chapter 1Current State of Accidents at Universities
1.1 Introduction
While rapid progress is being made in science and technology, many faculty members, researchers, graduate and undergraduate students have been killed in accidents involving chemical experiments in laboratories of universities and academic institutions (hereafter referred to as “universities, etc.”). However, the total number of accidents that have occurred in university laboratories worldwide remains unknown, and in many cases, similar accidents have been repeated several years later at other universities. This is because time has passed without a paradigm shift or fundamental change in laboratory safety measures, and universities around the world have not made progress in collaborating to prevent accidents.
According to a questionnaire survey conducted by the author, there are few established accident investigation and analysis methods or uniform rules for accident investigation and analysis in universities, and even when accident investigation and analysis is conducted, the 4Ms (man, machine, media, and method) analysis tool mainly applied in the manufacturing industry is used. In many cases, investigation reports and lessons learned from accidents that occur within universities are never published (Fukuoka 2022a).
In addition, there are no international organizations, such as the International Maritime Organization (IMO) or the International Civil Aviation Organization (ICAO), whose objectives mainly include accident prevention. It is essential for accident investigation and analysis to determine which accident models are applicable to the industry to which it belongs and to conduct the investigation and analysis using the methods associated with those accident models. If an inappropriate accident model is used in an accident investigation, the mechanism leading to the accident will be incorrectly analyzed and the resulting safety recommendations will be misdirected in terms of preventing accident recurrence. However, many chemical accident investigations in university laboratories have not been discussed based on accident models, although case studies have been carried out. Therefore, the lack of uniform methods for accident investigation and analysis raises doubts not only about the accident factors themselves derived as a result of the accident investigation but also about the derived data results, even if the accident factor data are statistically processed (Fukuoka and Furusho 2022).
For many universities to use the lessons learned from accident analyses to reduce accidents, accident investigations must be scientific, investigation and analysis methods must be standardized, and a large amount of accident data must be collected and analyzed. The approach to this is to bring together universities, etc. around the world to formulate investigation and analysis methods and rules, including the preparation of accident investigation reports, to provide education and training in investigation and analysis methods, and to establish a forum for sharing information to reduce accidents.
This book clarifies the problems that need to be solved to prevent the recurrence and prevention of accidents faced by universities, etc. in comparison with other industries, and describes approaches that can be adapted to universities, etc. First, as a prologue to the content discussed in Chapter 2 and below, issues related to accident prevention in universities, etc. obtained compared with other advanced industries are discussed.
In the subsequent chapters, the term “accident” refers to events involving injuries or fatalities occurring during educational and research activities within universities, etc., while “incident” refers to events threatening the safety of individuals other than accidents during educational and research activities, or events causing damage to facilities or equipment used during activities. Near misses are included within incidents.
1.2 Background
A wide variety of accidents occur in universities around the world, including explosions during chemical experiments in research laboratories. It is not possible to estimate how many accidents occur in university laboratories around the world, as the data itself are not published. The following is an excerpt from a review article by Ménard and Trant (2020) published in Nature Chemistry:
Over the past ten years, there have been several high-profile accidents in academic laboratories around the world, resulting in significant injuries and fatalities … However, the study of academic lab safety is still underdeveloped and necessary data about changes in safety attitudes and behaviours has not been gathered … More than ten years on from Sangji’s death, we can conclude that there is no evidence of sweeping, fundamental changes, nor of major paradigm shifts in how academic lab safety is approached within the discipline.
However, in the field of ship and aircraft accidents, a social transformation, a paradigm shift, took place in the second half of the twentieth century with regard to accident prevention. This involved the following multiple factors (Fukuoka 2023):
Shift from human error to human factors
Development of the software, hardware, environment, liveware (SHEL) model
Development and global adoption of safety management systems (SMSs)
Development of accident models, such as the Swiss cheese model, which can explain the mechanisms of organizational accidents
Shift from Criminal Investigation to Safety Investigation
The trigger for these factors was a series of serious accidents in various industries in the 1970s and 1980s that affected society as a whole. In the chemical industry, 28 employees were killed in a chemical plant explosion in Flixborough, United Kingdom, in 1974, and thousands of citizens were killed by acute poisoning in Bhopal, India, in 1984 when a chemical plant released methyl isocyanate, while the exact number of victims was never determined.
In the maritime industry, 193 passengers and crew were killed in the 1987 capsizing of the ro-ro vessel Herald of Free Enterprise (HFE), which was traveling to and from the Strait of Dover. In the aviation industry, in 1985, Japan Air Lines (JAL) Flight 123 crashed into Mount Osutaka, killing 520 passengers and crew and leaving only 4 survivors, making it the worst single aircraft accident. In the space industry, in 1986, the US space shuttle Challenger exploded just 73 seconds after liftoff, killing all seven crew members on board.
1.3 Modes and Effects of Human Error
Human error was actively studied by Norman, Rasmussen, Reason, and others in the mid to late twentieth century, and findings were developed and established as follows.
1.3.1 Norman’s Theory
Norman (1988) emphasized that people make some errors in error-prone situations that are unrelated to specific personal characteristics. He distinguished between slips and mistakes. In other words, slips are errors of behavior, while mistakes are errors of thought.
1.3.2 Rasmussen’s Theory
Rasmussen, Duncan, and Leplat (1987) extended Norman’s theory and defined three types of performance and error. They are skill-based, rule-based, and knowledge-based. He states that people display different behavior at these three different levels.
At the skill-based level, it is an automatic method and is used when performing tasks that are routine and highly trained. The rule-based level is used when specific situations are encountered and there are already agreed rules for performing these actions. The knowledge-based level is used when a new situation is encountered that has not been experienced before. This is the highest performance level and involves people working very slowly, using all the resources imprinted in their memory through trial-and-error learning.
Rasmussen emphasizes that the process of people making decisions is not linear and that in real life people often shortcut the process. As a result, he states that the three levels outlined above can coexist at any time.
The three performance aspects of everyday life are explained, covering the process of learning to ride a bicycle. When riding a bicycle for the first time, children learn in detail from their parents and friends how to ride a bicycle, how to balance, when and how to brake, etc. When they actually ride a bicycle, they find it difficult to control it and keep going, so they try to learn to ride a bicycle through a process of repeated trial and error. This process is called knowledge-based performance. After a number of training sessions, the operating skills of riding a bicycle gradually improve and they are able to get out on the road. When they come across a traffic light, they stop, making sure that the rule is that they should not proceed at a red light. They also check that they are traveling on a particular side of the road, as they have learned from their parents. This process is called rule-based performance. They ride their bicycles every day, and after a few months, they become so familiar with it that they no longer need to pull out the bicycle maneuvering and traffic rules from their memory each time and apply them in practice. In particular, they can ride without having to think about how to maneuver it in their minds. When they encounter a red light, they are able to achieve their objectives by skipping rigid procedures experienced in the knowledge-based and rule-based performance, such as stopping reflexively. This process is called skill-based performance.
1.3.3 Reason’s Theory
Reason (1990) expanded on Rasmussen’s theory. He states that slips and lapses are behavioral errors involving skill-based performance. Mistakes and violations are errors in people’s intentions, whereas mistakes occur in either rule-based or knowledge-based performance. He coined the concept of latent conditions, which was previously called latent error, and distinguished between active failure, which was previously called active error, and latent situations. Active failures are committed by operators and manifest themselves quickly, while latent conditions are caused by higher levels, such as designers and managers, and the existence of latent conditions is not exposed in the organization and lies dormant for a long time. He states that active failures are affected by latent conditions and that accidents occur due to rare combinations of these errors. This theory of his was the source for the development of the Swiss cheese model.
1.3.3.1 Slips, Lapses, Mistakes, and Violations
According to Reason (1990), errors are classified into four categories. An unintended act that relates to a person’s attention and an error that occurs at the stage of execution is called a slip. Errors that are unintended acts related to memory and occur at the stage of consideration are called lapses. Errors that occur because the action was intended but the plan itself was not fit for purpose due to a design error at the planning stage, and the action was carried out according to the plan, are called mistakes. If a rule exists, the act is a violation. The violation addressed here is a negligent violation without malice. For example, wearing personal protective equipment (PPE) is common knowledge and a safety rule in chemical experiments, but this applies to cases where researchers do not wear the designated PPE because they think it would be safe at their own discretion. Explained from a different perspective, the question is: “Was the action carried out a planned action?” and if the answer is “no,” then an unintended action has been executed. The error in this execution is a slip or lapse. A slip is the result of not paying sufficient attention when executing an action. A lapse is a planned action not being executed due to an error in memory. “Was the action carried out a planned action?” If the answer is “yes” to the question, then the intended action was carried out and a mistake was made. The error occurred at the planning stage, which means that there was a problem in the decision-making process. Mistakes may progress more unnoticed by people than slips and lapses, and a longer period of time may pass between the execution of a mistake and its detection.
1.3.3.1.1 Case Study of Slips
Many readers probably start their day with a cup of coffee every morning. They turn on the coffee machine, pour water, set the capsules in place, place the coffee cup in place, and press the button for their choice of blend or espresso, and their coffee of choice is ready. However, as they become accustomed to this action, doing the same thing over and over every morning, they inadvertently press the espresso button without setting the capsule in place. Only hot water is poured into the coffee cup. You realize for the first time that you did not set the capsule.
Hotels have bathrooms, some with fixed shower heads (overhead showers) and some with portable shower heads. To use a fixed shower head, turn the left handle, shown in
Figure 1.1
, backward. To use the portable shower, turn the same handle toward you as for the fixed shower. The handle is marked with a “Caution! Hot Water” sign. The temperature of the hot water is adjusted using the handle on the right. The author was drenched by cold water coming out of the fixed shower head when he accidentally turned the handle because he wanted moderate hot water. Given the warning sign “Caution! Hot Water,” one imagines that many people would have been drenched head-first in boiling water against their will.
Figure 1.1 Showerheads and their handles as a sample of slips. The left-hand handle is enlarged in the photograph on the right. The handle is marked with a red label with a warning. The large disk-shaped shower head directly above the handle is fixed. To the right of the fixed shower head is the portable shower head. These photographs were taken by the author in the same hotel in December 2022, including Figure 1.2.
Figure 1.2 A bathroom tap that can prevent slips. The tap in the left photograph is enlarged in the right one. The blue and red markings indicate whether water or hot water is supplied.
Shower equipment that does not cause people to make errors would be as follows. The temperature is adjusted with the left handle and the shower head is selected with the right handle, which has a different shape. There is no room for error. This shows that human error is largely due to external factors as well as human causes.
However, the washroom in the same hotel was designed to prevent slip when using water and hot water. Figure 1.2 shows that on the tap handle, turning the handle in the blue direction provides water and turning the handle in the red direction provides hot water. One can get water or hot water without confusion. It can be seen that by matching a person’s intended behavior with their thoughts, by adding shapes, signs, and diagrams to the equipment, it is possible to prevent people from making errors.
1.3.3.1.2 Case Study of a Lapse
You walk from your room to the kitchen with the intention of taking a teacup from the kitchen cabinet, but you enter the kitchen and stop, unable to remember what you came here to do. You go back to your room again and try to remember what you went to the kitchen to do, only to realize that it was to pick up the teacup.
You set a single document in the photocopier to make copies and have completed the specified quantity of copies, but forget to remove the document from the photocopier. A colleague informs you that the document is still in the photocopier and you realize that you forgot to take the document out.
1.3.3.1.3 Case Study of a Mistake
Many people commute to work by train, bus, or other public transport to the university or workplace. When universities are on summer holidays, public transport timetables can change significantly. Without realizing this, they leave home as usual and wait at the bus stop to board their usual bus, but the bus does not come. A notice is posted on the bulletin board at the bus stop, and they learn for the first time that the bus they are using is temporarily out of service due to the university summer holidays. They rush to board another bus but are late for the scheduled work time. They realize that this error was an error in their very plan to use their usual bus to go to the university.
1.3.3.1.4 Relationship Between Errors and External Factors
Grandjean (1969) conducted a scientific experiment on behavioral failure. He measured the frequency of errors when the arrangement of the control panel and the stove was changed. When the arrangement perceived by the person matched the arrangement of the stove and control panel, it was tested 1200 times and not a single error occurred. The three patterns with slightly different arrangements were tested 1200 times and errors occurred in the range of 76–129 times. In other words, it can be demonstrated that individuals are less prone to error when their cognitive processes align with the configuration of the control and display sequences.
The controls in the steering seats of many vehicles, such as cars, trailers, airplanes, and ships, are designed with full consideration of human characteristics, such as a person’s physique, range of vision, and thinking patterns, so that errors are unlikely to occur.
1.3.3.2 Impact of Human Error
The examples from everyday life described in Section 1.3.3.1 show that the impact of the error only affects the person who made the error and does not cause significant harm. However, failures of caution, that is slips, have also occurred in university experiments and chemical plant operations and other industries. At a university, a timer and temperature were set on a heating device to heat a sample during an experiment, thinking that the temperature was displayed in Celsius, but the temperature was displayed in Fahrenheit instead of Celsius, causing the temperature to be set much higher than intended, resulting in the sample overheating and smoke coming from the heating device. The alarm in the laboratory was triggered and security guards responded to the incident, which did not lead to a fire.
According to the US Chemical Safety Board (CSB 2021), the accident investigation body, during the silicon emulsion production process in a chemical plant, an employee put calcium hydroxide, a pH-adjusting substance that should not have been mixed in, into a drum in which silicon hydride was stored. This generated hydrogen gas, which mixed with air, and the presence of an ignition source in the plant caused an explosion and fire, killing four employees and wrecking the plant. The drums used to store the three chemicals were of the same color and shape (55-gallon blue plastic drums), identified only by labels, and the incompatible substances were stored in close proximity. The drums were all the same shape and color, so employees could not tell them apart.
The CSB determined that the risk of the chemical combination was not defined in the US Occupational Safety and Health Administration (OSHA) standards, which was also a contributing factor in the accident. The CSB (2021) recommended that the US OSHA, the chemical policing body, review its chemical standards and even influenced legal action.
In a memory failure, lapse, during a leisure dive activity, a diver jumped in without opening the tank valve before entering the water, which made it difficult for him to breathe in the water. In the preparation before the scuba dive started, he inadvertently forgot to open the tank valve.
In an example of a vessel accident, a pilot was maneuvering a cargo ship from one port to another, when he assumed that buoy A, which marked the safe passage boundary, was buoy B, which marked the route exit, and after passing buoy A, he changed the vessel’s course to the right and continued sailing, resulting in the ship grounding in shallow water. The pilot stated that he changed course as usual, thinking he had already passed buoy A and reached buoy B, which shows the exit of the passage. The accident affected many stakeholders, including the cargo ship grounded; the crew; the cargo ship’s company; the Coast Guard, who maintains the buoys and enforces maritime laws and regulations; the port authority, who manages the safety of passages in the port; and the salvage company that handles the grounding ship and the property insurance company (Japan Transport Safety Board 2010).
1.4 Transition from Human Error to Human Factors
In the second half of the twentieth century, the increasing complexity of socio-technical systems, industrial structures, and accident causal factors made it no longer possible to apply the conventional approach to accident analysis, which is centered on human error. In other words, the idea of preventing accidents by clarifying the systemic problems that induced the error or failed to prevent the accident, rather than focusing attention on the person who caused the human error and attributing the cause of the accident, has spread, particularly in Europe and the United States. In the field of accident model, sequential accident models, such as the domino theory, which are characterized by a mechanism in which the factors of an accident appear sequentially and linearly and then accidents occur, are no longer able to clarify the actual state of accidents and all the factors behind them. The “Tenerife tragedy,” an aircraft accident that occurred at a small regional airport in Tenerife Island, located off the western coast of Africa, marked the turning point for this issue and the shift in the focus of accident investigation analysis to human factors. See Chapter 3 for the development of the accident model.
1.4.1 The Tenerife Tragedy
1.4.1.1 Summary of the Accident
In March 1977, two 747 jumbo jets of Dutch Airlines (KLM) and Pan American Airways (Pan Am) collided head-on on the runway at Los Rodeos Airport, Tenerife, Spanish Canary Islands, killing 583 passengers and crew. The accident is still the worst in aviation history. Immediately after the accident, the Air Line Pilots Association (1977), an association of pilots, published an Aircraft Accident Report, based on interviews with those involved and evidence collected. The details of the accident based on this report are as follows, showing that a number of factors combined to cause the crash.
1.4.1.2 Circumstances and Factors Leading to the Accident
Following a terrorist explosion at the terminal of Las Palmas Airport in the Canary Islands, a well-known resort destination, the airport authority temporarily closed the airport and instructed aircrafts destined to land at Los Rodeos Airport. The airport authority lifted the closure of Las Palmas Airport and resumed landings after the airport was declared safe, but in the meantime, Los Rodeos Airport was crowded with large and small aircrafts that had been instructed to change their landing sites. Los Rodeos Airport is a regional airport with one runway located at 621 m altitude, where stratocumulus and cumulus clouds frequently occur and visibility at the airport can be poor. After the reopening of Las Palmas Airport, passenger aircraft parked at Los Rodeos Airport took off one after another for the airport, but there were aircrafts parked on the taxiway.
The Air Traffic Control (ATC) first instructed KLM aircraft to proceed in the opposite direction on the runway to the takeoff preparation point. The ATC then instructed Pan Am aircraft to proceed in the same reverse direction on the runway and turn left onto the taxiway at C3, which was located near the midpoint of the runway. KLM aircraft reached the designated point at the end of the runway and awaited clearance for takeoff from ATC. Meanwhile, Pan Am aircraft was to proceed to the taxiway at point C3, but crew of Pan Am aircraft either misunderstood the instructions from ATC or overlooked C3 and continued backward down the runway toward the KLM aircraft. The Air Line Pilot Association, which investigated the accident, analyzed in its report that it was physically impossible for Pan Am, a large aircraft, to enter C3, which required a change of course at a sharp angle. It is recorded that the visibility at this time was approximately 100 m. ATC had no radar equipment installed and relied on visual observation with the naked eye to determine the situation at the airport. Both aircraft crew could not see the other, nor could ATC see the situation of the two aircrafts on the runway.
The KLM captain communicated with ATC and attempted to throttle up for takeoff, assuming that the message from ATC telling him how to fly after takeoff was the answer to the takeoff clearance. At this point, the crew’s flight engineer informed the captain that he did not have takeoff clearance, but the captain prepared the aircraft for takeoff. The flight engineer did not firmly reiterate to the captain that he did not have clearance for takeoff. KLM aircraft had a team of three: the captain, the copilot, and the flight engineer. The personal relationship was such that there was an authority gradient between the three, as the captain was a person of authority at KLM and also a training instructor. The authority gradient hinders the sharing of useful safety information within the team; the captain may have been in a hurry to takeoff, as KLM aircraft planned to fly back to the Netherlands after arriving at Las Palmas Airport and could have exceeded the working time limit under Dutch working rules if he had not taken off early at Los Rodeos Airport.
Radio communication between the ATC and KLM or Pan Am aircrafts was poor, with interference during conversations, making some conversations inaudible. The ATC is a native Spanish speaker and his English was mixed with Spanish, making some parts difficult to understand. At the time of the accident, the aviation terminology used by air traffic controllers and crews was not standardized worldwide, and misleading and ambiguous terminology was used in communication. As a result, there was a mixture of assumptions.
The KLM aircraft then began its run on runway for takeoff. Shortly before the collision, the Pan Am, which was turning left on the runway toward C4 next to C3, suddenly appeared in the KLM captain’s field of vision and he raised the nose of the aircraft in an emergency takeoff attempt. However, the lower fuselage of the KLM aircraft collided with the upper fuselage of the Pan Am aircraft, causing the KLM aircraft to crash and burn and most of the Pan Am aircraft to be destroyed and set on fire; only some of the Pan Am passengers and crew survived. The contributing factors that caused the accident are listed in the following:
Change of destination (S)
Inconsistent (ambiguous) aviation terminology (S)
Radio communication status between crew and ATC (H)
Radar not installed (H)
Narrow taxiways (H)
Weather conditions at high-altitude airports and reduced visibility (E)
Authority gradients, availability of time, assumptions, and low flight time of KLM captain (Lc)
Communication between crew (Lc)
Communication between crew and ATC (Lp)
Language used by crew and ATC (Lp)
Verbal guidance given to aircrafts by ATC (Lp)
Los Rodeos airport is located at a high altitude, which makes it vulnerable to weather conditions, and at the time of the accident, a new airport was under construction at a lower altitude. The Spanish and Dutch Accident Investigation Authorities have also published accident investigation reports on the accidents that occurred in Tenerife. The details of these reports are not included in this section, as this section discusses the mechanism of the accident, in particular the relationship between human factors and the occurrence of the accident.
The SHEL model indicates that the accident was not the result of a linear sequence of accident factors, as proposed by the domino theory. Rather, it suggests that a number of factors were present prior to the accident. Furthermore, the model indicates that the KLM captain’s error, which was a mistake, triggered a number of latent conditions to emerge simultaneously, resulting in the accident. Figure 1.3 is a model of the accident mechanism on the KLM side. At the time of accident, KLM’s SMS was not yet in place and crew risk management was not functioning. The accident trajectory shows that the accident occurred after all the multiple layers of defense had been penetrated.
Figure 1.3 The mechanism of the Tenerife tragedy. At the time, KLM’s SMS and crew risk management were not functioning and are shown as dashed lines. The accident trajectory is indicated by the red arrow.
Source: Adapted from Fukuoka (2024).
1.5 Development of the SHEL Model
Five years before the Los Rodeos Airport Jumbo Jet accident, in 1972, Professor Edwards developed and published the SHEL model, which included social components related to the accident. SHEL stands for software, hardware, environment, and liveware. Liveware, representing human elements, includes Central liveware (Lc) and Peripheral liveware (Lp). The SHEL model was modified by Hawkins (1987).
The SHEL model has a total of five blocks in the shape of a cushion centered on Lc. The jagged edges of each block do not coincide with their relative edges, indicating that the relationships between the two elements are not well established. The model was originally used as a method for the comprehensive collection of evidence on human factors and others in aircraft accident investigations. The model has since been adopted by the shipping industry and used as a tool to prevent omissions in the collection of evidence during the accident investigation phase. Since the late 1990s, the model, together with the Swiss cheese model, has been adopted by the ICAO and the IMO, two specialized UN agencies, and has been included in manuals for ship and aircraft accident investigation and is still used in accident investigation.
The SHEL model differs from human error in that it focuses on the errors and mishaps of the person who caused the accident (hereafter referred to as the “operator”) and includes all factors related to the accident that caused the human error. This includes not only the company to which the operator belongs but also regulatory authorities, inspection bodies, relevant private bodies, international organizations, etc. and all relevant social components involved in the accident can be identified. By viewing the accident as an event that occurred in the context of the interrelationship of all these social components, the clear picture of the underlying factors can be visualized.
1.5.1 Elements of the SHEL Model
The following is a brief description of each element of the SHEL model, adapted to accidents occurring at universities, etc. Details of the SHEL model are given in Chapter 5.
Software S is employed by faculty, researchers, students, research groups, and fieldwork research teams at the time of an accident at the accident site. It encompasses a range of materials, including procedures, protocols, checklists, experimental plans, dive plans, climbing plans, maps, and instructions on the use of PPE and emergency response plans.
The letter H refers to the hardware associated with the accident. This encompasses a range of equipment, including laboratory apparatus, gas storage tanks, high-pressure cylinders, ancillary equipment such as piping, laboratory equipment such as centrifuges and beakers, and other types of laboratory apparatus. It also includes diving equipment used for scuba diving and climbing equipment used for mountaineering.
