Systematic innovation provides a more methodical approach to problem solving than typical trial and error methods. It involves thoroughly understanding the problem, searching various knowledge databases for similar past solutions, and adapting those solutions to the specific problem. The approach aims to find the root cause of problems and eliminate trade-offs through design. It also considers trends and demands to develop the most ideal solutions over time. The theory of inventive problem solving breaks down innovation priorities and maturity curves to guide the development of disruptive versus incremental innovations.
Adaptive Work Systems: A Perspective on the Evolution of Socio-Technical Systems in Today's World presentation given by Stu Winby at 2012 STS Roundtable Conference in Canterbury, UK
Capabilities: The Bridge Between R-&-D - 21may14Ian Phillips
Research can seem very isolated from Product Development. This work illustrates the role of Research in establishing Capabilities; Capabilities which will subsequently be used in Product Development. Thus showing Research to be important in the ecology of a healthy business.
How to enable innovations in Enterprise Mobility ?ANOOP KUMAR P
Innovations in enterprise mobility are challenged by forces of ecosystem. This presentation tries to structure the areas of innovations and approaches to address them. The scope of innovation spans from devices to business processes. An organized focus will help derive new values via innovations.
Adaptive Work Systems: A Perspective on the Evolution of Socio-Technical Systems in Today's World presentation given by Stu Winby at 2012 STS Roundtable Conference in Canterbury, UK
Capabilities: The Bridge Between R-&-D - 21may14Ian Phillips
Research can seem very isolated from Product Development. This work illustrates the role of Research in establishing Capabilities; Capabilities which will subsequently be used in Product Development. Thus showing Research to be important in the ecology of a healthy business.
How to enable innovations in Enterprise Mobility ?ANOOP KUMAR P
Innovations in enterprise mobility are challenged by forces of ecosystem. This presentation tries to structure the areas of innovations and approaches to address them. The scope of innovation spans from devices to business processes. An organized focus will help derive new values via innovations.
Innovation pathway for infrastructure solutionsChris Jurewicz
The intent was to provide a high-level pathway for innovation which can be adapted for more specific purposes in different areas of civil engineering. The pathway applies equally to innovation in engineering processes, products and in design.
This presentation is a living document which will be updated as we learn more and gain experience. The main sources for this knowledge were a literature review and practitioner workshops, backed by experience on several projects.
Webinar - Design Thinking for Platform EngineeringOpenCredo
Design Thinking is revolutionising the delivery of next-level digital services with best-of-breed product design and user interface principles ensuring close alignment with users and making services a joy to use.
While much of this success has been in the delivery of customer-facing services, there is untapped potential when it comes to delivering frictionless experiences for the internal users of your infrastructure services – promising business value through increased productivity and reduced frustration in your development and operations teams.
Check out the slides from our webinar on approaching platform engineering with a design thinking mindset.
Field Studies as evaluation method for socio-technical interventions in Techn...Viktoria Pammer-Schindler
Field studies as evaluation method for socio-technical interventions in Technology-Enhanced Learning.
Much research in TEL is design work – i.e., the research team designs an intervention that is intended to support learning. This intervention needs to be evaluated to show the extent to which this goal has been reached; and to gain additional insights that are sought for. Field studies are one main type of evaluations. They are challenging to set up; and in case of a bad study design cannot be easily repeated due to the effort and cost of running a field study. The goal of this lecture and workshop is
To provide a blueprint for field studies as evaluation method for socio-technical interventions in technology enhanced learning
To present a hierarchical principle of evaluating learning interventions– based on Kirkpatrick & Kirkpatrick: Usage/observable activities – Learning – Impact on task/work performance – Impact on organization (in workplace learning/applicable to settings in which individual learning impacts a wider social entity)
To have students plan a field study for their own PhD in rough lines individually
To discuss their plans with peers and the lecturer, as well as other senior researchers who may be present – i.e., students will get feedback on their own plan
The blueprint for field studies is to evaluate in a hierarchy of research questions/evaluation level: First, one assesses the observable (learning) activities that are carried out – in particular how and whether participants adhered to the prescribed intervention; this helps understand the success of the intervention and it is possible to identify problems. Second, one assesses concrete learning outcomes – insights that are generated. Thirdly, one assesses a change in behaviour, and fourthly a change in performance. In parallel, a mix of qualitative and quantitative methods should be used – this allows on the one hand statistical comparison (pre/post; between groups). On the other hand, one can get in depth explanatory insights.
Innovating new products using multiphysics modeling comsol2012-bangaloreRajveer Shekhawat
A widely recognized reality in industries around the world is that of being consistently innovative. Without it the survival is too difficult and can be only short lived. And so only the engineers working on new products in industrial research labs have been striving to enhance the product value for customer by innovating. However, it has been very difficult task till now as the ways of validating new products have been lengthy and costly. One has mainly resorted to crude or scaled down prototypes or at most modeling or simulation of limited functionality of the product being worked upon. The validation of the prototypes has been very difficult and not very reliable as these did not represent full functionality of the product. Further to iterate over various design choices (design space), one has to depend on large number of prototype variants derived using Design of Experiments theory.
The tools like COMSOl and ANSYS have been around for long but been restricted mostly to the researchers investigating various phenomenon. These days however, they have been able to handle multiple domains simultaneously through coupling mechanisms. With ever increasing capability of such tools, we are thus witnessing application of these to real-life products and systems which had been too complex so far for such task. This is more so as the real-life products do not spawn over to single phenomenon or physics but comprise of multiple phenomena over multiple domains. Hence these tools are coming to the aid of the practicing engineers to evolve new products or innovative products.
In this presentation, a few examples of products which involve expertise and understanding of multiple physics phenomena and their interactions for their further evolution and enhancement are discussed. How the use of COMSOL Multiphysics has been helpful in solving complex design aspects saving extensive time and effort would also be delved into in some detail.
Recommender systems support the decision making processes of customers with personalized suggestions. These widely used systems influence the daily life of almost everyone across domains like ecommerce, social media, and entertainment. However, the efficient generation of relevant recommendations in large-scale systems is a very complex task. In order to provide personalization, engines and algorithms need to capture users’ varying tastes and find mostly nonlinear dependencies between them and a multitude of items. Enormous data sparsity and ambitious real-time requirements further complicate this challenge. At the same time, deep learning has been proven to solve complex tasks like object or speech recognition where traditional machine learning failed or showed mediocre performance.
Explore a use case for vehicle recommendations at mobile.de, Germany’s biggest online vehicle market. Marcel shares a novel regularization technique for the optimization criterion and evaluates it against various baselines. To achieve high scalability, he combines this method with strategies for efficient candidate generation based on user and item embeddings—providing a holistic solution for candidate generation and ranking.
The proposed approach outperforms collaborative filtering and hybrid collaborative-content-based filtering by 73% and 143% for MAP@5. It also scales well for millions of items and users returning recommendations in tens of milliseconds.
Recommender systems support the decision making processes of customers with personalized suggestions. These widely used systems influence the daily life of almost everyone across domains like ecommerce, social media, and entertainment. However, the efficient generation of relevant recommendations in large-scale systems is a very complex task. In order to provide personalization, engines and algorithms need to capture users’ varying tastes and find mostly nonlinear dependencies between them and a multitude of items. Enormous data sparsity and ambitious real-time requirements further complicate this challenge. At the same time, deep learning has been proven to solve complex tasks like object or speech recognition where traditional machine learning failed or showed mediocre performance.
Join Marcel Kurovski to explore a use case for vehicle recommendations at mobile.de, Germany’s biggest online vehicle market. Marcel shares a novel regularization technique for the optimization criterion and evaluates it against various baselines. To achieve high scalability, he combines this method with strategies for efficient candidate generation based on user and item embeddings—providing a holistic solution for candidate generation and ranking.
The proposed approach outperforms collaborative filtering and hybrid collaborative-content-based filtering by 73% and 143% for MAP@5. It also scales well for millions of items and users returning recommendations in tens of milliseconds.
Event: O'Reilly Artificial Intelligence Conference, New York, 18.04.2019
Speaker: Marcel Kurovski, inovex GmbH
Mehr Tech-Vorträge: inovex.de/vortraege
Mehr Tech-Artikel: inovex.de/blog
This is a session on Lean Principles for Agile Teams presented at ERUC in October 2013. This is the deck used with the LEGO building block exercise PDF.
Research is now where manufacturing has been 100 years ago. We are about to setup automated production lines of research results which will profoundly affect the whole research sector. It rises many important questions e.g. how far human thinking and cognitive functions can be replaced by machines, how to adopt higher education and many other.
17. SYSTEMATIC INNOVATION The Theory of Inventive Problem Solving Solutions change - functions stay the same The evolution of systems is not random - it follows repeatable patterns Somebody, somewhere has faceda similar problem to yours and managed to solve it… …all you need to do is find and adapt their solution 4
18. SYSTEMATIC INNOVATIONHow it works: WORLD’S BEST SOLUTIONS A Generic Solution A Problem Like Mine My Specific Problem My Specific Solution 5
22. Ideality time Without SysInno: Infinite options Ideal final result ‘perfect, free, now’ With SysInno: Best practice Game changing High impact Medium impact Finite options 9
25. Emergence - Trend towards Webs & Fibres 12 ? riveted steel tank FRP cistern ferro-concrete tank ? rolled metal tube CFRP driveshaft pultruded tube 3D mesh with optimised fibre orientation homogenous sheet 2D mesh active elements
31. S-Curve Innovation Priorities Identifying disruptive Innovations Identify functions achieved by other technologies Technology transfer (out) Incremental Innovation Process Innovation Problem solving micro – cost, efficiency Problem solving macro - Performance Technology Transfer (in) Maturity (Ideality) IP analysis IP fencing Problem solving – Main useful Function time 14
32. Maturity Curves Modularadaptivesystems INCREASING IDEALITY 3rd GEN….. Compactsegmentedsystems 2nd GEN The timing and characteristics of each S-curve jump is predictable Stratifiedtank systems 1st GEN TIME 15
33. Resource & Stakeholder Research Explore prevailing attitudes, trends & aspirations among the relevant: Technologies Regulatory authorities Markets Stakeholders 16
34. SUPER-SUPER- SYSTEM SUPER- SYSTEM SYSTEM Space SUB- SYSTEM SUB-SUB- SYSTEM Time PRESENT NEAR-TERM PAST MID-TERM PAST LONG-TERM PAST NEAR-TERM FUTURE MID-TERM FUTURE LONG-TERM FUTURE 17
41. Thank you! Contact: Tony Owens, Director Shibumi Consulting Ltd ++353 (0)1 442 9609 towens@shibumi-consulting.net www.shibumi-consulting.net pragmatic innovation solutions
Editor's Notes
Systemlink looked at a range of limitations and inconvenience factors in determining how to improve SystemZone.Multigenerational product roadmap first MultiZone then ZoneAloneProduct cost and installation time issues with SystemZone dominated the development of MultioneZoneAlone is a more radical product innovation which introduces new physical effects to provide radically better regulation of zone outflow temperatureStaged adoption of hydrolysis-resistant plastic materials by lowest risk route possibleProgressive integration of discrete hydronic components e.g. nonreturn valves and pumps
Hydronic Manifolds SummaryMain Useful Function:Pressure ‘neutralisation’ - allow parallel connection and operation of hydronic sub-circuits without ‘crosstalk’Uses:Integrate diverse heat sources with minimal control complexityFacilitate deployment of zoned systems Two distinct generations seen so far:Tank-like systems – employ principle of buoyancy (thermal stratification) to segregate hotter and cooler fluid regions in common vessel. Disadvantages: size, cost, convenience, energy efficiency (heat transfer between hotter and cooler fluid masses) DUNSLEY-BAKER NEUTRALISER c.1982; Patent EP00085475 etcSegmented systems – employ twin fluid manifolds interlinked for pressure equalisation to segregate hotter and cooler fluid regions in common vessel. Smaller, cheaper, easier to plumb, improved efficiency. But… still costly, uses many discrete components, no modularity, heavy… SYSTEMZONE c. 1996; US06092734 etcThird generation systems being introduced now driven by usual cleantech drivers - material and energy waste reduction.3. Highly segmented systems – modular, lighter materials, much improved temperature regulation, improved energy efficiency, additional HVAC applications.MULTIZONE™ Q1 2010MINIZONE™, ZONEALONE™ 2010 Q3, Q4Others 2011
Computational fluid dynamic simulation used extensively during product development to understand:Internal pressure lossesThermal mixing behaviourNon-return valve behaviourThermal capacity of manifoldStructural simulation using finite element methods used to determine:Pressure vessel performance of metal caseworkApproximate non- return valve component behaviour, forces and stressingPresent development efforts aimed at validating simulation results and implementing accelerated life tests.Field testing commencement by year-end 2009.
Initial collaboration focused on proof of principle modelling, performance and life testing.Symbiotic relationship with active Thermo-Fluids research group led by Dr Anthony Robinson.Strong support from the State enterprise support agency Enterprise Ireland.Systemlink anticipates a bright future for high level RD&I in Ireland.Thank You!