Academia.eduAcademia.edu

Figure 15 – uploaded by Gerardo De MariA

See full PDFdownloadDownload figure
Fig. 18. Schemes and layouts for project engineers. Fig. 17. Airplane Operating Manual (Aircraft Flight Manual scheme for pilots).

Figure 18 Schemes and layouts for project engineers. Fig. 17. Airplane Operating Manual (Aircraft Flight Manual scheme for pilots).

Related Figures (21)

psychotherapy, engineering and economics. This theory was established as a science by Ludwig von Bertalanffy, Anatol Rapoport, Kenneth E. Boulding, William Ross Ashby, Margaret Mead, Gregory Bateson and others in the 1950's. Among all the mentioned scientists’ share, Ludwig von Bertalanffy’s contribution, a Viennese professor of biology 901-1972), was definitely the most influencing regarding the definition of system theory. He worked to identify structural, behavioral and developmental features common to particular classes of living organisms. One effective approach was to ook over the empirical universe and pick out certain genera phenomena, which are found in many different disciplines, and to seek to build up general theoretical models relevant to these phenomena, e.g., growth, homeostasis, evolution. The whole content of Bertalanffy's ideas was gathered into a Genera Systems Theory. Since he defined a general system as any theoretical system of interest to more than one discipline, his view could look at the world in terms of relationships and integration. In his scientific script systems are seen as integrated wholes whose properties cannot be reduced to those of smaller units. Instead of concentrating on basic building blocks or substances, the systems approach emphasizes the principles of organization. Every organism, from the smallest bacterium through the range of plant, animals and human beings - plus the family, society and the planet as whole - is an integrated whole and thus a living system. That is why an important aspect of systems is their intrinsically dynamic nature. Their forms are not rigid structures but they are flexible yet stable manifestations of underlying processes. System thinking is process thinking; form becomes associated with process, interrelation with interaction, and opposites are unified through oscillation. These oscillations are the ingredient that makes the development of systems unpredictable. Dynamical System Theory helps us dealing with this lack of predictability. Fig. 1. A history map of the leading scholars and areas of research in complexity science.
psychotherapy, engineering and economics. This theory was established as a science by Ludwig von Bertalanffy, Anatol Rapoport, Kenneth E. Boulding, William Ross Ashby, Margaret Mead, Gregory Bateson and others in the 1950's. Among all the mentioned scientists’ share, Ludwig von Bertalanffy’s contribution, a Viennese professor of biology 901-1972), was definitely the most influencing regarding the definition of system theory. He worked to identify structural, behavioral and developmental features common to particular classes of living organisms. One effective approach was to ook over the empirical universe and pick out certain genera phenomena, which are found in many different disciplines, and to seek to build up general theoretical models relevant to these phenomena, e.g., growth, homeostasis, evolution. The whole content of Bertalanffy's ideas was gathered into a Genera Systems Theory. Since he defined a general system as any theoretical system of interest to more than one discipline, his view could look at the world in terms of relationships and integration. In his scientific script systems are seen as integrated wholes whose properties cannot be reduced to those of smaller units. Instead of concentrating on basic building blocks or substances, the systems approach emphasizes the principles of organization. Every organism, from the smallest bacterium through the range of plant, animals and human beings - plus the family, society and the planet as whole - is an integrated whole and thus a living system. That is why an important aspect of systems is their intrinsically dynamic nature. Their forms are not rigid structures but they are flexible yet stable manifestations of underlying processes. System thinking is process thinking; form becomes associated with process, interrelation with interaction, and opposites are unified through oscillation. These oscillations are the ingredient that makes the development of systems unpredictable. Dynamical System Theory helps us dealing with this lack of predictability. Fig. 1. A history map of the leading scholars and areas of research in complexity science.
Fig. 2. A visual, organizational map of complex systems broken into seven sub-groups.
Fig. 2. A visual, organizational map of complex systems broken into seven sub-groups.
Fig. 4. Earth’ circulation: an example of dynamic system. Fig. 3. Graphical representations of some fields characterized by non-linear dynamics and complexity
Fig. 4. Earth’ circulation: an example of dynamic system. Fig. 3. Graphical representations of some fields characterized by non-linear dynamics and complexity
Fig. 8. Likelihood scale definition.
Fig. 8. Likelihood scale definition.
Fig. 5. Astrodynamics studies: an example of dynamic system.
Fig. 5. Astrodynamics studies: an example of dynamic system.
Two kinds of risk assessment matrix and an example of the likelihood scale definitions are shown.
Two kinds of risk assessment matrix and an example of the likelihood scale definitions are shown.
Fig. 7. Risk matrix with color codes. Fig. 6. Risk matrix with numbers, letters and color codes.
Fig. 7. Risk matrix with color codes. Fig. 6. Risk matrix with numbers, letters and color codes.
Fig. 10. Risk classification matrix (see explanation below).
Fig. 10. Risk classification matrix (see explanation below).
Fig. 9. Probability of occurrence definition (see explanation below).
Fig. 9. Probability of occurrence definition (see explanation below).
Resilience Engineering is a new complex way to approaching safety and it is based on the following paradigm: air crashes and fatalities occur out of the same reasons why flight operations successfully guarantee a good level of safety (see the brief case study following the paragraph about automation for further explanation). Erik Hollnagel underlines the importance of weak signals emerging from the daily activities to better understand how to improve all the safety levels in high complexity organization (Hollnagel et al., 2006). As we explained in the introduction, the main feature of complex systems is their dynamic stability/instability equilibrium; in short, you must move to be balanced. Resilience is what makes these systems robust and, at the same time, flexible. In Physics, and especially in the Science of Materials, it is the ability of an object to absorb the external perturbations, keeping its internal organization/characteristics unvaried; this is due to the property of the structure to absorb energy when it gets elastically deformed and to release this energy upon unloading. The maximum energy the object can absorb without creating a permanent distortion is the modulus of resilience. Fig. 11. Modulus of resilience: beyond this value a permanent distortion of the system occurs.
Resilience Engineering is a new complex way to approaching safety and it is based on the following paradigm: air crashes and fatalities occur out of the same reasons why flight operations successfully guarantee a good level of safety (see the brief case study following the paragraph about automation for further explanation). Erik Hollnagel underlines the importance of weak signals emerging from the daily activities to better understand how to improve all the safety levels in high complexity organization (Hollnagel et al., 2006). As we explained in the introduction, the main feature of complex systems is their dynamic stability/instability equilibrium; in short, you must move to be balanced. Resilience is what makes these systems robust and, at the same time, flexible. In Physics, and especially in the Science of Materials, it is the ability of an object to absorb the external perturbations, keeping its internal organization/characteristics unvaried; this is due to the property of the structure to absorb energy when it gets elastically deformed and to release this energy upon unloading. The maximum energy the object can absorb without creating a permanent distortion is the modulus of resilience. Fig. 11. Modulus of resilience: beyond this value a permanent distortion of the system occurs.
Fig. 12. Ready to “receive the stress of bad circumstances ”!!
Fig. 12. Ready to “receive the stress of bad circumstances ”!!
Fig. 13. Elements of a basic resilient system. A good behavior in aviation comes from a base of mental/physical health on which technical/non- technical skills and positive attitude are built. For aeronauts these are the minimum items they have to “carry” everyday at work in order to safely operate in heterogeneous crew and proactively prevents incidents/accidents. This shows how a resilient system has far deeper roots compared to what everyone of us can think. Every crewmember’ routine can influence the outcome of flight operations and the future of the resilient system.
Fig. 13. Elements of a basic resilient system. A good behavior in aviation comes from a base of mental/physical health on which technical/non- technical skills and positive attitude are built. For aeronauts these are the minimum items they have to “carry” everyday at work in order to safely operate in heterogeneous crew and proactively prevents incidents/accidents. This shows how a resilient system has far deeper roots compared to what everyone of us can think. Every crewmember’ routine can influence the outcome of flight operations and the future of the resilient system.
Fig. 14. Resilient can ride the risk!! The same principle applies at the organizational level. To safeguard the succession of every phase of flight, robustness and flexibility can be accomplished only with the use of professional judgment, adjusting the inputs for the actual conditions and coping with the unexpected. In the event of any irregularities, the organization, like a physical object, will be ready to “receive the stress of bad circumstances” and to react elastically avoiding most of the catastrophic consequences. The capability of the organization to create Fig. 15. An example of a resilient system: the system actuates a continuous flow of info to enhance the quality of the output.
Fig. 14. Resilient can ride the risk!! The same principle applies at the organizational level. To safeguard the succession of every phase of flight, robustness and flexibility can be accomplished only with the use of professional judgment, adjusting the inputs for the actual conditions and coping with the unexpected. In the event of any irregularities, the organization, like a physical object, will be ready to “receive the stress of bad circumstances” and to react elastically avoiding most of the catastrophic consequences. The capability of the organization to create Fig. 15. An example of a resilient system: the system actuates a continuous flow of info to enhance the quality of the output.
Fig. 16. Two common representations of the Anthonys Pyramid. It can be seen as the pyramid of safe operations, where more complex tasks are assigned to the top in terms of less people able to conduct them, less available resources and less margin for mistakes. In modern aviation there is the tendency to leave the lead level to automation and limit the human being 8 tasks to a mere control.
Fig. 16. Two common representations of the Anthonys Pyramid. It can be seen as the pyramid of safe operations, where more complex tasks are assigned to the top in terms of less people able to conduct them, less available resources and less margin for mistakes. In modern aviation there is the tendency to leave the lead level to automation and limit the human being 8 tasks to a mere control.
Indeed, the project engineer and manufacturer manual point out several useful symbols to the comprehension of the process ongoing. Their system descriptions, lately in a pure
Indeed, the project engineer and manufacturer manual point out several useful symbols to the comprehension of the process ongoing. Their system descriptions, lately in a pure
Fig. 19. Schemes and layouts for flight test engineers. Inputs and outputs are logically connected and in some cases, e.g. on the right side of the figure (in Italian), physics concepts related to characteristic equations are added.
Fig. 19. Schemes and layouts for flight test engineers. Inputs and outputs are logically connected and in some cases, e.g. on the right side of the figure (in Italian), physics concepts related to characteristic equations are added.
Fig. 20. Scheme and layouts for maintenance, usually for long maintenance checks, usually called “heavy maintenance”. Those used for transit maintenance are more simple, sometimes just algorithmic stepped procedures.
Fig. 20. Scheme and layouts for maintenance, usually for long maintenance checks, usually called “heavy maintenance”. Those used for transit maintenance are more simple, sometimes just algorithmic stepped procedures.
Fig. 22. Samples of simulink schemes and matlab files (they are not related to each other). Quality of the picture is not important here. What counts is to sho how more complex are these concepts of control engineering compared to the simple design given to final operators. Getting used to the logic of these contr engineering tools would possibly give future pilots the chance to better understand automation. Another useful notions for pilots would be those related to Control Engineering. Understanding a common Simulink framework (for the definition, see end of this paragraph) would give crew the chance to see:
Fig. 22. Samples of simulink schemes and matlab files (they are not related to each other). Quality of the picture is not important here. What counts is to sho how more complex are these concepts of control engineering compared to the simple design given to final operators. Getting used to the logic of these contr engineering tools would possibly give future pilots the chance to better understand automation. Another useful notions for pilots would be those related to Control Engineering. Understanding a common Simulink framework (for the definition, see end of this paragraph) would give crew the chance to see:
580 California St., Suite 400
San Francisco, CA, 94104
© 2025 Academia. All rights reserved