Some technologies are simple like a cup or hammer, some are complicated like a circuit board or car, but some are truly complex such as large information systems, supply chain networks, sustainable urban environments, health care systems or advanced financial services. These complex engineered systems are defined by consisting of multiple diverse parts that are highly interconnect and autonomous.
This course is a comprehensive introduction to the application of complexity theory to the design and engineering of systems within the context of the 21st century, from the bigger picture of why we should care to key architectural considerations, It brings together many new ideas in systems design to present an integrated paradigm and set of principal to the design of complex systems.
A new design paradigm- In the first section of the course we will explore some of the major themes that are shaping the design and engineering of systems in the 21st century, such as the rise of sustainability, information technology, the revolution in services and economic globalisation, these will all provide a backdrop and reoccurring set of themes that will be woven into our discussion. This section will also give you an overview to complexity theory and the basic concepts that we will be using though out the course, such as the model of a system, a framework for understanding complexity and a definition for complex systems.
The last section of this model will give an overview to complex systems design providing you with a clear and concise description of what a complex engineered system is and how this new paradigm in design differs from our traditional approach.
Key concepts- Next we introduce you to the key concepts within this new domain, we will talk about services and product-service systems, designing synergistic relations in order to integration diverse components and one of the key takeaways form this entire course the idea of abstraction as a powerful tool for solving complexity.
Design Principals- In the third module to the course we discuss the primary principals that should govern our approach to designing complex systems. Firstly networks with these highly interconnected systems networks are their true geometry, understanding them and being able to see the systems we are designing as networks is one of our key principal. Secondly we will look at adaptive systems and how I.T. is enabling the next generation of technologies that are responsive, adaptive and dynamic, allowing for self-organisation and a new form of bottom up emergent design. Lastly in this section we will also cover the key mechanisms of evolution and how it effect the lifecycle to the system we are designing.
Systems Architecture- In systems architecture we begin to change gears to talk about the more practical mechanics of how to design complex systems based around a new systems architecture paradigm that has arisen within I.T. over the past few decades what is called Services Orientated Architecture, in this section we will discuss platform technologies and their internal workings, modular systems design and Event Driven Architecture which is particularly well suited to the dynamic nature of the systems we are developing.
Design Methods- Lastly we present a series of lectures on the design method or process best suited to complex systems design. In this module you will be introduced to design thinking that represents a repeatable set of stages in the design process for solving complex problems.
In this lesson we are going to start the course off by taking a look at the bigger picture that is the environment or context within which we design and develop systems in the 21st century. Many factors point to the conclusion that we live in a time of transition, an unprecedented change, this change is both fundamental, rapid and multidimensional, The overarching paradigm that is often used to understand this change is that of a transition from an industrial age to a post-industrial information age, in this video we will discuss the key drivers that are part of this transition including, the rise of sustainability, the rapid expansion of economic globalisation, information technology and the huge growth in the services that has taken place over the past few decades.
This lesson will give you an overview to the area of complexity theory for designers and engineers. Starting with a look at Systems Thinking which is a more holistic way of seeing the world one that is characterised by the belief that the parts of something are intimately interconnected and explicable only by reference to the whole. We will also discuss the model of a system and look at complexity along four key parameters namely: quantity, diversity, interconnectivity and autonomy. By understanding both what systems are and what exactly complexity is we will be able to formalise a definition for complex systems and wrap up by giving some example.
Complex systems design is a new area that is still very much in formation but in this lesson we will give a 2000 foot view of the domain. Starting by talking a bit about what design and systems design are we will then build upon this basic understanding of what design is to clearly illustrate our traditional approach that rests upon the assumptions and framework of modern science. By having a clear understanding of this traditional approach we will be able to see why it begins to fail and break down when dealing with systems that are highly interconnected, highly dynamic and whose components have some degree of autonomy. In this lesson we will also try to get a grasp on what exactly a complex engineered system is and have some examples at hand.
Service systems can be characterised by the value that results from the interaction between their components. A car sharing service might be a good example of this, by connecting people, technology and information we are able to deliver the end user with close to nothing but the pure functionality or services of personal mobility. Services follow a very different logic to that of our traditional product centric wold, in this section we discuss the services paradigm, talk about what exactly a service system is, give some examples and itemise the key characteristics to service systems.
Abstraction in its main sense is a conceptual process by which general rules and concepts are derived from the usage and classification of specific examples. Conceptual abstractions may be formed by reducing the information content of a concept or an observable phenomenon, typically to retain only information which is relevant for a particular purpose. For example, abstracting a leather soccer ball to the more general idea of a ball retains only the information on general ball attributes and behavior, eliminating the other characteristics of that particular ball. In a type–token distinction, a type (e.g., a ‘ball’) is more abstract than its tokens (e.g., ‘that leather soccer ball’).
In the natural world, synergistic phenomena are ubiquitous, ranging from physics (for example, the different combinations of quarks that produce protons and neutrons) to chemistry (a popular example is water, a compound of hydrogen and oxygen), to the cooperative interactions among the genes in genomes, the division of labor in bacterial colonies, the synergies of scale in multi-cellular organisms, as well as the many different kinds of synergies produced by socially-organized groups, from honeybee colonies to wolf packs and human societies: compare stigmergy, a mechanism of indirect coordination between agents or actions that results in the self-assembly of complex systems. Even the tools and technologies that are widespread in the natural world represent important sources of synergistic effects. The tools that enabled early hominins to become systematic big-game hunters is a primordial human example.
Networks are emerging as the structure to our systems of organisation in the information age, though amazingly very little was know about them until quite recently. Within just the past few decades network theory has embarked upon a scientific quest for a deeper understanding of the nature of networks. Network theory asks basic questions about the degree of connectivity within a network, the structure of networks and the properties that these various structures give rise to. In this section we will discuss the networked nature to complex engineered systems and how they are largely defined by the structure and make up of the networks that constitute them.
Adaptation refers to both the current state of being adapted and to the dynamic evolutionary process that leads to the adaptation. Adaptations contribute to the fitness and survival of individuals. Organisms face a succession of environmental challenges as they grow and develop and are equipped with an adaptive plasticity as the phenotype of traits develop in response to the imposed conditions. The developmental norm of reaction for any given trait is essential to the correction of adaptation as it affords a kind of biological insurance or resilience to varying environments.
1. Adaptation is the evolutionary process whereby an organism becomes better able to live in its habitat or habitats.
2. Adaptedness is the state of being adapted: the degree to which an organism is able to live and reproduce in a given set of habitats.
3. An adaptive trait is an aspect of the developmental pattern of the organism which enables or enhances the probability of that organism surviving and reproducing.
Self-organization is a process where some form of global order or coordination arises out of the local interactions between the components of an initially disordered system. This process is spontaneous: it is not necessarily directed or controlled by any agent or subsystem inside or outside of the system. It is often triggered by random fluctuations that are amplified by positive feedback. The resulting organization is wholly decentralized or distributed over all the components of the system. As such it is typically very robust and able to survive and self-repair substantial damage or perturbations. In chaos theory it is discussed in terms of islands of predictability in a sea of chaotic unpredictability.
Co-creation is a management initiative, or form of economic strategy, that brings different parties together (for instance, a company and a group of customers), in order to jointly produce a mutually valued outcome. It views markets as platforms for firms and active customers to share, combine and renew each other’s resources and capabilities to create value through new forms of interaction, service and learning mechanisms. It differs from the traditional passive consumer market of the past.
Evolution is not simply a biological phenomena it is a process through which all adaptive systems evolve overtime whether they are social, natural or technical and it is defined by a few key elements, such as the creation of variety, adaptation and selection. Product life cycle is a corollary to this in that it describes the key stages through which engineered systems go through on their journey from cradle to grave. In this video we will discuss both and how we can harness the mechanisms of design in the systems we are developing to create truly sustainable technologies that internalise change and evolve overtime
Service-oriented architecture (SOA) is a design pattern based on distinct components providing application functionality as services to other applications via a protocol. This is known as service-orientation. It is independent of any vendor, product or technology. A service is a self-contained unit of functionality, such as retrieving an online bank statement. Services can be combined by other software applications to provide the complete functionality of a large software application. SOA makes it easy for computers connected over a network to cooperate. Every computer can run an arbitrary number of services, and each service is built in a way that ensures that the service can exchange information with any other service in the network without human interaction and without the need to make changes to the underlying program itself.
Platform technology is a term for technology that enables the creation of products and processes that support present or future or past development. It establishes the long-term capabilities of research & development institutes. It can be defined as a structural or technological form from which various products can emerge without the expense of a new process/technology introduction. In computing platforms, for example, computer hardware serves as platform for an operating system which in turn is a platform for Enterprise Infrastructure Software which in turn is a platform for application software. Transport infrastructure similarly serves as platform for vehicles. A platform technology increases the ease of manufacture. Fewer parts/sub-assemblies need be designed, made, and kept in inventory, and assembly workers don’t need so much training
Modular design, or “modularity in design”, is a design approach that subdivides a system into smaller parts called modules or skids, that can be independently created and then used in different systems. A modular system can be characterised by functional partitioning into discrete scalable, reusable modules, rigorous use of well-defined modular interfaces and making use of industry standards for interfaces.
Besides reduction in cost (due to less customisation, and shorter learning time), and flexibility in design, modularity offers other benefits such as augmentation (adding new solution by merely plugging in a new module), and exclusion. Examples of modular systems are cars, computers, process systems, solar panels and wind turbines, elevators and modular buildings. Earlier examples include looms, railroad signalling systems, telephone exchanges, pipe organs and electric power distribution systems. Computers use modularity to overcome changing customer demands and to make the manufacturing process more adaptive to change (see modular programming). Modular design is an attempt to combine the advantages of standardisation (high volume normally equals low manufacturing costs) with those of customisation. A downside to modularity (and this depends on the extent of modularity) is that low quality modular systems are not optimised for performance. This is usually due to the cost of putting up interfaces between modules.
Event-driven architecture (EDA) is a architecture pattern promoting the production, detection, consumption of, and reaction to events. An event can be defined as “a significant change in state”. For example, when a consumer purchases a car, the car’s state changes from “for sale” to “sold”. A car dealer’s system architecture may treat this state change as an event whose occurrence can be made known to other applications within the architecture. From a formal perspective, what is produced, published, propagated, detected or consumed is a (typically asynchronous) message called the event notification, and not the event itself, which is the state change that triggered the message emission. Events do not travel, they just occur. However, the term event is often used metonymically to denote the notification message itself, which may lead to some confusion.
Protocols and contracts are the mechanisms through which elements in engineered systems interacted and cooperated, they represent a well defined syntax, semantics, and synchronisation of communications and behaviour. Communications protocols have to be agreed upon by the parties involved. To reach agreement, a protocol may be developed into a technical standard. Through these contracts and protocols we can essentially automate the interaction between components thus greatly facilitating the exchange of resources, cooperation and possibility of self-organisation
Design thinking stands for design-specific cognitive activities that designers apply during the process of designing. Design thinking has come to be defined as combining empathy for the context of a problem, creativity in the generation of insights and solutions, and rationality in analyzing and fitting various solutions to the problem context. According to Tim Brown, CEO and president of IDEO, the goal of Design Thinking is “matching people’s needs with what is technologically feasible and viable as a business strategy” The premise of teaching Design Thinking is that by knowing about how to successfully approach and solve difficult, multi-dimensional problems – more specifically, effective methods to ideate, select and execute solutions – individuals and businesses will be able to improve their own problem solving processes and skills. There is also significant academic interest in understanding how designers think and design cognition. The first formal academic research symposium on Design Thinking was organized at Delft University of Technology, The Netherlands, in 1991, and has developed into a regular series.
In this slide show we will delve deeper in the Design Thinking process giving practical guidents for each stage in the process. Content by the Institute of Design at Stanford
Think Academy is an e-Learning site dedicated to the area of systems thinking and complexity theory, our mission is to take the world of complexity and make it accessible to all. Systems and complex can be intimidating subjects with many sophisticated concepts, this is why we believe it is important to always start with the most essential, simplest elements of a subject making sure that students come away with a solid understanding of the core concepts behind each area. As Einstein said "Make everything as simple as possible, but not simpler"
Courses are curated and presented by Joss Colchester. Joss has extensive experience within the domain of complex systems both within academic research(mathematical modeling of complex system + network analysis) and has many years practical systems engineering experience(designing and developing complex web based information systems). He has a passion for taking abstract and complex concepts and making them concrete and accessible to as broad an audience as possible by combining clear and effective graphics with well structured course content.