Why is it necessary to discuss the role of people in control rooms? For many of us it has been obvious for decades that we need to create a harmony between technology and the people involved in steering, controlling, and managing the technology. Countless accidents with very dramatic and severe consequences have been blamed on ‘the human factor’. The human and environmental tragedies of Bhopal, Brent Spar, Chernobyl, the Exxon Valdez, MinaMata, and Three Mile Island show what can go wrong when humans engage with machines. However, very early we learned and understood that the operator was not to blame. The reasons for the catastrophes were defined as the lack of compatibility between people and technology. In essence, the interface between technology and people did not match. Today we talk about a lack of usability and ergonomic considerations. Earlier we used words like ‘human factors’ and ‘human engineering’. If some human agents need to be blamed it is the designer and the purchaser of the systems for overlooking the critical importance of technology/human factors. Most readers of this book are aware of these factors, but in some parts of the world this remains a little understood area of knowledge. A ‘nice-looking’ control room is more prized as a place to show and impress visitors. This seems to imply that form is of greater importance than functionality and use. This is obviously not so. A careful design of the interrelationship between the operators and the control systems and its controlled processes is essential for a safe and optimal operation.
Every 15 to 20 years we see a paradigm shift in industrial and technological processes. The introduction of new technologies into organisational processes requires organisations (and their members) to ‘change paradigms’ about how they work and behave (Clarke and Clegg, 1998). The inertia in this process of change is related to many factors, but probably the most important is the need for return on investment. Rapid developments in technology (including information technology [IT]) create an urgent need for organisations to develop new skills, competencies, and knowledge (Ivergard, 2000; Paulsson, Ivergard, and Hunt, 2005). The three elements of technology are: as a driver of organisational transformation, as an enabler to deliver that transformation, and as a change agent of the organisation to include new skills and competencies. For many (if not all) organisations, a critical issue is not in keeping up to date with the development of technology per se but in developing competencies to enable the organisation to gain full advantage of the technology.
The full potential of technology will only be realised if the organisation succeeds in adopting new business processes and working routines into the organisation as new ways of doing things (McKenney, 1995; Clarke and Clegg, 1998). Thus it becomes critical for organisations to develop new competencies in employees who use the new technology in their work. Introducing technologies into organisational processes requires organisations (and their members) to ‘change paradigms’ about how they work and behave (Clarke and Clegg, 1998). This includes learning the skills needed to utilise new technologies in the workplace (Edmondson et al., 2003). Technology is thus a key driver for workplace learning as employees need to develop skills for managing and operating the newly-adopted technology (Pisano, 1994; Paulsson et al., 2004). Learning the skills to perform using the new technology is critical if the technology is to be used for optimum benefit.
However, primarily, the new technology in itself has to be adapted to the existing competence and knowledge infrastructure of the organisation. This is the ergonomic approach to technological change. The importance of this symbiotic relationship between technology and people in organisations is discussed by Ivergard (2000). Technology is normally not an aim in itself but a means to achieve other aims, for example, to improve efficiency of learning or to reduce cost of learning. Inherent in learning at work are many possibilities of integrating learning technologies as a part of the control system of industrial and administrative processes. As such, technology has been a key driver for learning at work (Pisano, 1994; Edmonson et al., 2003). Intelligent technologies need to learn and adapt to the skill, knowledge, habits, and culture of the operators. Artificial intelligence (AI) is a good example. AI is a new and potentially very fruitful area of application. However, it is obvious that e-learning and other forms of learning technologies can never—or, at least, very rarely—‘stand alone’ for learning process. Rather, it has to be combined with other methods to create a holistic process of learning.
To build a good society we need to create harmony and balance between people and between people and technology. To create a good production environment in balance with nature we also need a good harmony and balance between people and technology. It is important for decision makers to understand these points. It is necessary to define the problem, to recognise the benefits of worker participation and motivation to design and create, and to take appropriate action to engage these.
In less than a generation, we will probably see different ‘new generation’ control centres. One technological development is likely to be a vertical high-tech Al-supported centre automatically capable of optimising the processes according to preset control variables. The main task of the operator will be to continually update and upgrade the computer software and its survival systems.
The second might be an organic control system continuously supporting the operator’s tacit knowledge base and mental models of the process. It will be a balanced symbiosis involving a harmonious relationship between the human operator and the technological system. Here the operator uses all senses to support learning and systems knowledge. This will in turn be used to upgrade the systems software and hardware. In both cases the system will include corporate social responsibility (CSR) and environmental and business considerations.
In this handbook we have made the case, from various perspectives, of the need for usability and ergonomic design to be incorporated into control room design and use. With the increasing importance of control rooms as key components in the operations and management of businesses and governments, the competencies of the operators take on a new leading role. In this new and evolving situation the operator is not only handling a limited industrial process. The work in the control room is becoming a focal point for the success of many different types of organisations in, for example, business, trading, energy, environment, and government. From many of the latest control centres we have been investigating, it is clear that the levels of competence and necessary education of operators has increased. It is also clear that control centre tasks cover a larger perspective than in the past. As we have discussed elsewhere in this handbook, creative development tasks have become integrated into control centre work.
This trend is likely to continue and to expand. The advanced control centre of the future will also include top-level experts and senior executive decision makers. This will most likely be the case in government organisations as well as in business-orientated industries. This might also be the case in international organisations, such as the United Nations, the World Bank, and the Asian Development Bank. It is easy to see the advantage for top-level executives such as managing directors and presidents of large public and private organisations to have direct access to extensive databases and real-time process information presented on very large-scale wall displays.
Furthermore, the availability of simulation programs of macro-perspectives of business relations and business actions will help decision makers improve the quality of their decisions and predictions. This future type of control centre is also likely to create its own architecture—both physical and functional. The physical architecture of the control centre of the future will be a very challenging task for architects and designers.
 At the time of the first edition of this handbook, the concept of a process industry encompassed a whole variety of industries and companies that all had one feature in common. In these industries, the input (raw material) is processed, converted, or changed (often chemically and/or physically) in order to create the finished product. In process industries, it is also common for subprocesses to occur in some sort of flow, and for the progressions between the different elements to be more or less directly connected to each other. These subprocesses are often automated; that is, they occur without any direct intervention from a worker. Typical examples of process industries are the paper, electricity, food, gas, and petroleum industries. In all these industries the raw material and the finished product are very different, and although the work carried out by people in each system varies markedly, the principles of the organisation of work processes are the same. Since the first edition, there has been an explosion in information handling in all areas of business and society. Naturally, this has had implications for understanding the concept of process industries. The markets for trading of energy, natural resources, and environmental pollution are all, in a manner of speaking, kinds of process industries. The use of computers as well as information and computer technologies (ICT) is an important factor that adds on to this greatly expanded conceptualisation of process industries.
 An international research and consultancy company active in the field of ergonomics.
 According to the Swedish Electrical Standards (SEN 0106), a closed control system is not a regulated system when the control equipment consists of a person. The authors’ opinion is that this is not applicable here, where the same terms are used for both human and technical components. The concepts of a regulated system are therefore also used here for manual control with feedback.
 This is clearly related to the concept of tacit knowledge (see Schon, 1982).
 1 asb (apostilb) is the luminance of a white surface illuminated by 1 lux.
 In 1965, Gordon Moore, then R&D director at Fairchild Semiconductor and later cofounder of silicon chip manufacturer Intel Corporation, stated that the density of transistors that can feasibly be placed on an integrated circuit chip doubles every 18 months. This ‘law’ was later refined to suggest that technology increases in performance every 2 years (see, for example, Grove, 1990; Schaller, 1997).
 Deutsches Institut fur Normung (the German Institute for Standardisation).
 Standard white screen—This screen has a gain close to 1.0 and diffuses the projected light like a Lambertian diffuser (to give a similar brightness in all directions).
• Gained white screen—Gain is typically 1.2 to 1.8, and the viewing angles are reduced compared to the gain 1.0 screen.
• Tinted screens—Gain is typically 0.6 to 0.9. These screens appear grey, and they absorb a certain amount of the light and thereby maintain a better image black level.
• Gained tinted screen—Gain is typically 1.2 to 3.0. The screen appears ‘silver-like’ and while it has a good contrast ratio, it has very restricted viewing angles.
• Optical screen—Gain is typically 0.8 to 2.0. The contrast ratio is very high and the viewing angles can be very good, depending on the optical lens design. These screens are often limited in size, but can be tiled to the required image size.
 DLP is a registered trademark of Texas Instruments.
 Display of many different sources.
• Complete solution from one supplier: cube, software, controller.
• Compatibility with customer systems.
• Easily extendable, a lot of options.
• Perfect overview, high image quality.
• Flexible display, layout can be changed easily and quickly.
• Meeting of ergonomic and architectural requirements.
 Internal split controller available.
• Several inputs available.
• Local area network (LAN) connection possibility.
• Automatic colour and brightness correction to avoid the so-called chessboard effect and the colour differences between the individual cubes in a large screen wall.
• Automatic double-lamp systems.
• Minimal gaps between the projection modules.
• Possibility to build up walls in a curved arrangement with possibility to chooses different angles.
• Screens with nonglare surfaces and high viewing angles.
• Low noise level.
 Y refers to greyscale; C to colour.
 The colour red is normally used on instruments showing danger. In Chinese culture red is a ‘lucky’ colour and is thus not meaningful to represent danger. Obviously, in a globalised world, the colour red is used on stoplights and other ‘danger’ signals but in this context its use is a result of Western influences.
 See, for example, James Kanter, New Climate for Emissions Trading Turns Greed into Green, International Herald Tribune, 22 June 2007.
t See, for example, James Kanter, Stiff Rules Proposed on Carbon Trades, International Herald Tribune, 30 June-1 July 2007, page 14.
! Data from http://www. vattenfall. com, and from personal communication with managers at Vattenfall.
 ‘Personnel employed’ is calculated on the basis of man-years.
 Available at http://www. imo. org/includes/blastDataOnly. asp/data_id%3D1878/982.pdf.
 Red or filtered white light should be used to maintain dark adaptation whenever possible in areas or on items of equipment requiring illumination in the operational mode. This should include devices in the bridge wings.
• High contrast in luminance between the work area and surroundings should be avoided, i. e., luminance of the task area should not be greater than three times the average luminance of the surrounding area.
 Normal operation
 In general, people can only absorb a limited amount of information at any one time. For some types of learning, the content and process of training should therefore be divided up in some way into stages, so that not too much information is presented at once. However, there are exceptions to this general rule of thumb. When learners are expected to build up a tacit knowledge model of an industrial or administrative process, then the content can be holistic and highly information-intensive. This point will be discussed later.
• The demands made on speed and accuracy must be selected very carefully for the different training stages. For certain types of work where accuracy is very important, it is better to insist on high accuracy right from the start; speed can come later as skill level increases. In this case, exemplification of ‘good practice’ and feedback on the learners’ efforts to replicate good practice should clearly focus on accuracy. A good example here is learning a foreign language, where beginners need to make themselves understood to interlocutors at a basic level of pronunciation, vocabulary, and grammar as well as learning the basic sounds and shapes of the new language. For other types of work (including speed skills), the reverse may be better, i. e., to require the highest possible speed at the start and allow low accuracy and to let this improve as learning progresses (Clay, 1964).
 System or process level modelling—Object-oriented software is used to conduct flowsheet-based mass balance calculations. Balances and functionalities are often based on first principles and include water, pulp, energy, etc. This is the most commonly-used approach to process description and simulation. In most cases, the approach to process optimisation is still empirical. Many software packages are available. Klemola and Turunen (2001) have published a complete report on Finnish modelling and simulation software. A recent COST report also gives an overview of the current use of software by COST E36 members (Alonso, Blanco, and Negro, 2004). The unit operations are defined as objects in libraries that can be positioned on a worksheet. The relationships between the objects are defined by lines drawn between the objects. The functionality is defined within dialogues of the individual objects. The equation system built in the background is typically calculated with a sequential or a matrix solver (Mathworks, 2002; Goedsche and Bienert, 2002).
• Unit operation level—High fidelity models of single pieces of equipment or smaller functional groups. Typical examples are paper machine dryer models. These pieces of software are typically written in plain code like FORTRAN or C++. They either originate from the scientific community or from the equipment suppliers. A new trend is that suppliers try to incorporate these models into the flow-sheet-based software. A breakthrough was achieved by Andritz linking its submodels as. dll files to the process model