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We are in the age of the fourth industrial revolution, also known as Industry 4.0. The concepts of Industry 4.0 are being applied to safety management and are described as Safety 4.0. This article discusses the application of Industry 4.0 to safety management.

The first industrial revolution was marked by a transition from hand production methods to machines using steam power. The second industrial revolution involved the installation of extensive railroad and telegraph networks, which allowed for faster transfer of people and ideas, as well as increasing electrification, which allowed factories to develop the modern production line. The third industrial revolution involved the spread of automation through the use of electronics and computers.

The fourth industrial revolution is about digital transformation. It involves the synergistic combination of various digital technologies to create a new, fully digitalized manufacturing ecosystem. Industry 4.0 involves further automation and data exchange using technologies such as cyber-physical systems (CPSs), the industrial internet of things (IIoT), cloud computing, cognitive computing, artificial intelligence, and 3D printing. (See the glossary below for explanations of terms used.) Industry 4.0 blurs the lines between the physical, digital, and biological worlds. Given the role of computer systems and networks in Industry 4.0, cyber security is an essential aspect. Industry 4.0 has developed owing to the creation of new technologies, such as smart phones, increases in computer processing speed, and lower costs of digital systems.

These industrial eras are described as revolutions because they are transformational, that is, they completely change the manufacturing paradigm, which is certainly true for Industry 4.0. It is also true that Safety 4.0 will be transformational.


Industry 4.0 provides numerous benefits including:

  • Reduces operational costs

  • Reduces capital costs

  • Increases productivity

  • Increases worker efficiency

  • Improves product quality

  • Advances the pursuit of sustainability

  • Supports operational excellence

  • Reduces the need for people to work in hazardous environments or under adverse environmental conditions

  • Improves risk management

  • Improves EHS performance

  • Improves process safety

  • Improves time-to-market for new products and product upgrades

  • Improves workforce engagement and job satisfaction

  • Reduces the occurrence of human errors

  • Compensates for a reduced / less experienced workforce due to retirements

  • Delivers better decisions faster


Key themes and aspects of Industry 4.0 include:

  • Smart automation and decentralization - The use of smart machines that can self-monitor and analyze and diagnose issues without the need for human intervention.

    Decision making is decentralized using local intelligence and tasks are performed autonomously. Smart machines respond in real time.

  • Connectivity, communication, and interoperability - The ability of machines, devices, sensors, and people to connect and communicate with each other via the Internet of things (IoT) and the internet of people (IoP). New communication technologies are changing the way people communicate. Such connections permit a fast exchange of data without human intervention.

    Everything in an Industry 4.0 manufacturing system is linked in a digital ecosystem. Tasks and activities are accomplished with integration and communication across the workforce, between workers, between managers, and between managers and workers.

  • Big data, and analytics - It has become possible to generate vast amounts of data and information from all points in a manufacturing process but it has not been possible to easily collect and analyze the data and information and distribute it to the right people at the right time using conventional data management approaches to identify issues and facilitate process improvement.

    Big data approaches and analytics, made possible by the processing power of today’s computers, now enable such data and information to be processed and disseminated to facility personnel in a useful form in real time. Manufacturing data and information is an underutilized resource. Big data analytics provide a major opportunity for improvement in managing manufacturing operations. They enable the identification of trends and correlations that are undetectable to the human eye.

  • Data availability - Conventionally, data and information have been siloed according to facility areas and responsibilities. In Industry 4.0, the silos are broken to allow pooling of data and information to facilitate access by anyone who needs it and avoid data and information gaps.

  • Data accessibility - All facility personnel at all levels have real-time and on- demand access to the data and information they need. Data is pushed when needed.

    Personnel can view data and information from any tablet, smart phone, or computer terminal. Data are available on a facility’s processes, personnel, and assets. Data come from existing enterprise systems, connected personnel across the facility, and third-party sources.

  • Data visualization and contextualization - Data and information are presented in an easily understood form, often graphical, and in the context in which they are needed. Everyone works off the same data and information so there is only one version in use. A digital view is provided of facility conditions, activities, and operations.

  • Cloud computing - Makes it easier to distribute and access manufacturing data. However, it is not suitable for the storage of critical and/or sensitive information which should be stored securely on premises. Industry 4.0 allows for software technology to be deployed in the cloud, on premises, or both, as needed, to take advantage of cloud-based solutions while securing critical and/or sensitive information.

  • Technical assistance - Provide technical information to facility personnel on demand when it is needed. Facilitate communication with remote experts.

  • Virtualization - The digital creation of a virtual copy of a process or facility for use in various ways, for example, to examine the effects of changes before they are made to the physical plant. The virtualized view is visualized through a 3D interface.

  • Artificial intelligence - used in various ways. For example, machine learning algorithms can be used to find patterns in data, without being explicitly instructed to do so. Machine learning algorithms can monitor a system continuously and optimize the operation of processes as conditions change. Such algorithms can also learn from encountering unsafe scenarios, and adapt procedures to prevent their reoccurrence.

  • Augmented and virtual reality (AR and VR) - AR is used to supplement a user interface that represents real-life situations and data with helpful information in the form of visual, audio, or haptic signals. Real-time information provided through AR can help improve quality, efficiency, and safety.

    VR is used to produce simulations of the behavior of processes.

  • Cognitive and behavioral science - Application of the latest understanding of human cognition, decision making, and behavior and how they influence perceptions, culture, competency, and performance.

  • New digital equipment and technologies

    Wearables for personnel - Can monitor personal health and exposure to hazardous materials and environments, and track wearers.

    Smart personal protective equipment (PPE) - Electronic sensors in hard hats, eyewear, footwear, gloves, etc. can continuously collect and monitor data on the work environment, the user, and/or its own functioning.

    Voice recognition - Allows hands-free recording of information and issuing commands by people using tablets and other devices.

    Drones - Can act as data collection devices, for example, to carry out inspections. Such use is particularly beneficial when hazardous or difficult-to-reach areas are involved.

    Proximity sensors for vehicles - Sense when a vehicle gets close to an object to avoid collisions or keep the vehicle on track.

    Machine vision - Uses image processing to enable automated decision-making, for example, in automated inspections of equipment.

    Smart visors - Facilitate access to needed information.

    Intelligent autonomous robots - Collaborative robots (cobots) can be employed to help humans or other robots perform their tasks.

Fundamentally, Industry 4.0 is about data - its generation, collection, storage, transfer, processing, and use. These data operations are facilitated by new, updated, and existing technologies that are adapted to human use.


Industry 4.0 is based on data, technology, and behavioral science. In Industry 4.0, everything is intelligent, instrumented, and interconnected. Paper-based processes are converted to digital and piecemeal processes are unified in a connected digital system. Clearly, Industry 4.0 requires concomitant cultural change for its implementation, a process that needs to be properly managed.

Implementation of Industry 4.0 requires a smart integrated manufacturing management system (SIMMS) to act as the backbone of a smart manufacturing facility. The SIMMS collects and processes data and information from the manufacturing facility in real time and autonomously, or with human assistance, manages facility operations as an integrated set rather than disparate operations and activities. For example, Industry 4.0 enables:

  • Assistance with daily planning of activities

  • Identification of job conflicts

  • Assistance with shift turnover

  • Remote monitoring of assets and processes in real-time

  • Tracking and tracing of assets and people

  • Management of personnel competency

  • Promotion of situational awareness

  • Prediction of risks

  • Visualization of hazards


The technologies of Industry 4.0 can be deployed to benefit both occupational health and safety and process safety. Improvements are gained in managing occupational risks and the catastrophic risks of high hazard facilities. Safety 4.0 also facilitates the automation of compliance with regulations, standards, and certifications, which is particularly valuable when facing evolving requirements.

Safety 4.0 requires the introduction of new safety philosophies, more use of sensors to monitor process conditions and the integrity of safety systems, remote equipment automation, digital enhancements to improve human / machine interfaces, the integration of systems, advanced use of sensor data and data analytics, metrics that go beyond the use of simple leading and lagging indicators, and the use of cloud-based safety services. Field devices, portable safety devices, and intelligent wearables all feed data into a safety management system in Safety 4.0.

Safety 4.0 enables many safety improvements, for example:

  • Automation of many manual activities removes opportunities for human error while providing data that can be used to generate an immediate response to events when needed.

  • Continuous process monitoring provides the means to detect problems before any failures occur avoiding hazardous situations and production downtime.

  • Movement up the hierarchy of controls results from automation placing less reliance on administrative controls and helps to eliminate potential employee exposure to hazards.

  • Provision of assistance to people performing difficult or hazardous tasks.

  • Intelligent wearables allow facility personnel to more safely, reliably and efficiently accomplish their tasks.

  • Digital permits automate previous paper-based processes.

  • Digital inspections replace manual ones.

  • Big data and analytics identify important trends in operational data for safety improvements.

  • Process hazard analysis (PHA) analytics and big data enable PHA studies to be mined for insights into accident prevention and also provide valuable information for other process safety elements, such as mechanical integrity and operating procedures.

  • Safety records, such as past accident data can be analyzed to provide insights into how the severity and likelihood of incidents can be reduced.


Digital devices can communicate with smart phones designed for industrial use. Thus, facility personnel can automatically connect their industrial smart phone to, for example, a portable or fixed gas detector to provide immediate alerts in the event of a release.

Industrial smart phones and notepads can provide workers with on-demand instructions and visuals for performing tasks including lists of required tools and information on their use.

Worker competence can be improved through training that leverages virtual reality so that workers can experience tasks before performing them on live plant.

PPE can be embedded with sensors or radio-frequency identification (RFID) technology in order to collect and transmit data. Managers and workers can be automatically notified when workers are not wearing required PPE or not wearing it correctly.

Safety managers can view data transmitted from PPE and wearables on demand and in real time on their notepad, laptop, or smart phone. They can immediately determine which workers are using particular equipment or devices, whether the workers are qualified in its use, whether the equipment or device is fit for service, and they can view device readings.

Electronic confined space monitoring in real time can be used to monitor worker biometric values (heart rate, body temperature, breathing rate) as well as their exposure levels to toxics to alert workers and managers to a potentially dangerous situation, and to guide emergency rescue operations, if necessary.

Safety managers can run reports for the various data streams they receive from field devices and facility personnel. Trends in the data can alert safety managers to intervene in order to prevent the development of dangerous situations.

For the mechanical or asset integrity element of process safety, a particular smart device in a smart manufacturing facility, for example, a safety valve, can notify its failure or imminent failure to the SIMMS, which can then either take independent action, such as shutting down a unit or taking other corrective action, depending on the circumstances, or notify a responsible person to take action. The SIMMS can also initiate inspections or replacements of similar safety valves, including ordering needed replacements. Process safety incidents and downtime are reduced or avoided.

Please contact Primatech for information on a smart integrated manufacturing management system for Safety 4.0 applied to process safety (Smart PSMTM ). Learn how Industry 4.0 technologies apply to each element of process safety and how they can be managed with a SIMMS.


Artificial intelligence (AI) - The ability of a computer to perform tasks that are usually done by humans because they require human intelligence. Intelligent machines work and react like humans.

Augmented reality (AR) - A technology that merges interactions among humans and cyber-physical systems through the superposition of digital data on reality. It is a new form of human-machine interaction.

Big data - Refers to data sets that are too large for typical database software tools to effectively capture, store, and analyze. This is true for most manufacturing databases.

Big data analytics - The process of examining large and varied data sets, or big data.

Cloud computing - A technology that allows both digital data storage and computing. It refers to the on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct active management by the user.

Cognitive computing - Refers to computer hardware and/or software that mimics the functioning of the human brain and helps to improve human decision-making. Uses technologies such as artificial intelligence, machine learning, signal processing, natural language processing, speech recognition, object recognition, and dialog and narrative generation.

Cyber-physical system (CPS) - Consists of smart machines, information and data storage systems, and production facilities that are capable of autonomously exchanging information, triggering actions, and controlling each other independently. They form the basis of Industry 4.0 and are used to create smart factories.

Data visualization - The graphical representation of information in the form of a chart, diagram, or picture.

Interoperability - Represents a characteristic of a manufacturing system in which its components are capable of exchanging information with one another and using the information that has been exchanged.

Industrial Internet of things (IIoT) - Refers to interconnected sensors, instruments, and other devices networked together in industrial applications.

Internet of people - Refers to the digitalization of relationships between people and the collection, processing and application of personal data. It forms a network of collective intelligence and stimulates interactive communication among our digital selves through digital devices, the internet and sharing of data.

Internet of things - Refers to physical objects, for example, alarms, that are embedded with sensors, processing ability, software, and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks.

Machine learning - A core part of AI. It allows software to more accurately predict outcomes without explicitly being programmed.

Virtual reality - A simulated experience that can be similar to or completely different from the real world.

3D printing - The process of making a physical object from a three-dimensional digital model, typically by laying down many thin layers of a material in succession.

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