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Operational Analysis – A Thought Framework

Operational Analysis – A Thought Framework

One of the key tenets of Systems Engineering or Systemic Thinking is developing an understanding of how the system (or a product under development) is going to operate or behave under various scenarios. This leads to identification of the right set of functions, acceptance criteria’s, operational modes of the systems and constraints from the operational environment if any. These discoveries are then formulated in textual form as requirements. This skill of identifying the right dependencies, with operational environment, both which can be both spatial or temporal in nature often come by timeover a period of time, by living and breathing in the system domain. For example, an aerospace engineer who has been practicing the domain for decades might be an expert in the aerospace engineering, but if he/she is tasked to work in a medical device, it might be very difficult for them to even comprehend where to start! Another example to consider is that operational environments also change with time or with additional applications.

Apart from having the right domain expertise, frameworks can come handy. Frameworks or patterns are tools that allow one to think systematically and come up with all possible questions to be asked. Frameworks can act like a to do list. One of the frameworks we learned came across from MIT is “Get ready”, “Set” and Go. This is a simple phrase used in at the start of a race to synchronize timing, to command all the participants to start at the same time. However, it can be applied to a much larger context, and to almost anything really!

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The figures above is a nXm matrix to capture all actions that are done to achieve a mission. It describes the overall lifecycle of the operation phase. Let’s take an example to better understand the framework. 



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The table above is a ConOps for driving a vehicle to work or some destination. The whole lifecycle of operation can be further broken down by using the Ger Get Ready, set and go framework. It is important to note the difference between Getting Ready and Getting Set. The function of “getting set” part is executed just moments before the function “go” part. For Example herein the above mentioned scenario, before the driver starts driving the vehicle, he/she would enter the vehicle, get seated, put the seat belt on, turn the ignition on, and may be set the music and air conditioning.

The getting unset and unready functions concludes the operation. Once the whole operation is understood, it in is now easy to come up with establish required functions, identify stakeholders, identify risks, and come up with define associated requirements.

 

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Each step in ConOps can further lead to identification of associated risks, which can then be used for Risk mitigation planning. The below table shows example of Get Ready phase where the identified risks are shown marked in purple colour purple. 

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As can be seen with the example shared above, the ConOps is a pretty powerful tool to analyse a System of Interest and develop requirements for the further developing development and design ofing the system. 

If you are interested in understanding how to apply this within your organization, reach out to us at info@Blue-Kei.com. We specialize in systems engineering consulting, project executions, process adoptions, digital transformations and conducting workshops which are experiential and tailored to your needs. With systems engineering adoption you can address the complexity, manage evolving risks and bring transformation in communication within your organization through digitalization. 



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Electric Vehicles – Upcoming Trends & System Dynamics

Electric Vehicles - Upcoming Trends & System Dynamics

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Electric vehicles in India have finally crossed that threshold of being just talked about and being owned by a hand-full of people, and are now becoming an emerging trend. This is quite evident with the rising number of EV companies offering a range of EVs both cars and bikes. This trend continues to be backed by a rising number of start-ups jumping in the EV space.

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2020 however saw a dip in sales of EVs, which I believe happened with all the automotive sector due to pandemic. What is interesting to note is the total number of EV sales over years, which is still a long way to compete with fossil fuel based vehicles. I believe range of an EV is the single most important factor for customers not adopting EV as their primary vehicle of choice. If we can see a good range of EV, with a network of charging stations easily accessible, something similar to CNG stations, with quick charging, EV market can see a boom in demand, and our dependency on petrol and diesel cars can come down. In-fact Bill Gates talks about range and adoption of electric cars and technology trends here in a YouTube video.

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If we have a look at the Gartner hype cycle for Automotive technologies, the EV charging infrastructure is already going through a ‘trough of disillusionment’. This means, the hype about this is already over, but still needs investments to push this technology towards productivity, and maturity. This however is a global trend, and I truly believe we will see this happening in India as well.

With some systems thinking and with the help System Dynamics causal loop modeling, one can simulate what could be the makers or breakers for EV adoption in India. This will however require good judgement of policies and other factors. Factors, such as fuel prices, battery technologies, ecosystem, subsidies, etc.

Below is a very simple example of System Dynamics model for EV adoption I built using a free online tool called Loopy. The circles or nodes in the diagram represent all the factors we want to understand, or have an impact over others. Such as if want to understand how EV demand will grow over years, we capture other nodes which impact this adoption, and connect them together with causal loops. These causal loops have either positive or negative relationships, e.g. improvement in ‘Battery Technology’ will have a positive impact on ‘EV Demand’. The distance between nodes, or the length of loops, represent the rate at which the effect propagates in this tool. Few other factors that stood out while building this model were policies, and fuel prices. If the government pushes the write policies such as subsidies for purchase or such policies which could help accelerate battery technologies, we could see EV becoming mainstream, vehicle of choice for the masses, sooner than later!

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If you are interested in understanding how to adopt systems engineering and model based systems engineering practices within your organization, reach out to BlueKei Solutions team at info@Blue-Kei.com. We specialize in systems engineering consulting, project executions, process adoptions such as compliance to ISO15288, ARP 4754A, ISO 42020, digital transformations. We can also conduct capability development workshops which are experiential and tailored to your needs. With systems engineering adoption you can address the complexity, manage evolving risks and bring transformation in communication within your organization through digitalization and create the digital thread.

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The space-time continuum of the product development lifecycle

The space-time continuum of the product development lifecycle

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Imagine if the product development stage were mapped in terms of Time and Space. All the steps, all the artifacts that you develop during the lifecycle are placed spatially (in form of some documents). Their coming into being was through the time. The time that engineers, program managers and all the other stakeholders spent investing their energy and skills to build towards a saleable, marketable and long lasting quality product that their customers would cherish.

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Now what happens when something goes south? What happens if requirements aren’t met, the program is not on schedule, or an unfortunate event hampers the performance of your product for which there were no risk mitigation plans? Wouldn’t it be nice to travel back into the time and the space to look at all the artifacts you built through the complete development lifecycle ? Wouldn’t you wish this fabric of space-time continuum bent for you to travel back in time?

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Now imagine if all your hard work was captured in models and digital engineering tools, and connected, and managed for configuration and change, this would be your space-time fabric, your digital fabric. This will be a digital fabric where you will be able to travel in time and space both, to achieve the impossible, to reduce the turn-around time, to make fewer mistakes, and get things right the first time, and most importantly manage changes and help build resilient systems!

If you are interested in understanding how to adopt systems engineering and model based systems engineering practices within your organization, reach out to BlueKei Solutions team at info@Blue-Kei.com. We specialize in systems engineering consulting, project executions, process adoptions such as compliance to ISO15288, ARP 4754A, ISO 42020, digital transformations. We can also conduct capability development workshops which are experiential and tailored to your needs. With systems engineering adoption you can address the complexity, manage evolving risks and bring transformation in communication within your organization through digitalization and create the digital thread.