Welcome to the world of Infosys Engineering! It is a half a billion plus organization that takes pride in shaping our engineering aspirations and dreams and bringing them to fruition. We provide engineering services and solutions across the lifecycle of our clients’ offerings, ranging from product ideation to realization and sustenance, that caters to a cross-section of industries - aerospace, automotive, medical devices, retail, telecommunications, hi tech, financial services, energy and utilities just to name a few major ones.

May 25, 2019

Evolution of connected services organization

The connected services organization structure is an important structural element as enterprises embrace IOT and deliver solutions to its customers. There are many questions that enterprises need to answer as they design a structure that scales, sustains and importantly delivers. Executive sponsorship that is driven by strong governance is crucial since the new organization will be a change from the traditional structures

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April 22, 2019

The importance of engineering cloud-native and service based architecture layers for 5G Core Network Functions

Author: Balaji Thangavelu, Principal Consultant, Engineering Services

Service Oriented Architecture is a paradigm that has been around for a long time in the IT industry. Its success through deployments across vertical-industries has proven benefits  such as an extensible architecture, loosely coupled services, parallel development, higher availability and scalability. I am glad to see it crossing the boundary and coming into Network Engineering with the advent of Network Function Virtualization(NFV). Especially, its adoption into the 5G world in the form of 'Service Based Architecture(SBA)' is going to benefit the entire network ecosystem.

cloud-native approach to deploying the 5G Core VNFs(Virtual Network Functions) that follow the service based architecture model unlocks new stream of benefits for mobile operators. These benefits would be closely associated with scale and resilience of network functions. In simplistic terms, cloud-native is an approach to building and running applications that exploits the advantages of cloud computing delivery model. The cloud-native landscape is very vast and is constantly evolving.  Let us narrow down our focus and look at it in the context of 5G Core network VNFs.

In this blog post, I have shared my thoughts on how service-based architecture(SBA) and cloud-native implementation are an integral part to the overall design of the 5G core network. I have also highlighted key reasons as to why it is important to engineer these layers carefully to achieve the right balance between scale and service availability. Let us first understand a little bit about Service Based Architecture and cloud-native in context with 5G.

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March 25, 2019

IOT Edge of Tomorrow

The Edge of Tomorrow is a 2014 sci-fi movie starring Tom Cruise that's based on a time-loop and you can read reviews here. However, this blog is about the IOT edge of tomorrow which is as exciting about edge capabilities that are ever expanding. Before getting into a prediction mode, let us recap about what drives the edge in the IOT world - some of the factors are low latency, local computing and real time decision making, lack of reliable connectivity and proprietary protocol protection. I have elaborated on these aspects in my previous blog here. Industry experts, analysts, and my own experience the edge is here to stay and if anything will continue expand. 

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January 30, 2019

AR-VR at the intersection of SDN-NFV, 5G and Mobile Edge Computing - a practitioner's perspective

Author: Balaji Thangavelu, Principal Consultant, Engineering Services


In this blog post, I have shared my thoughts on how 5G, Software-Defined Networking & Network Functions Virtualization (SDN-NFV) and Mobile Edge computing (MEC) are an integral part of AR-VR(Augmented Reality and Virtual Reality) use cases, by taking a closer look at one of the interesting AR-VR use cases. I have also highlighted key factors that make it imperative for eco system players to engineer these technology areas with due considerations on some of the critical parameters.

Continue reading "AR-VR at the intersection of SDN-NFV, 5G and Mobile Edge Computing - a practitioner's perspective" »

January 9, 2019

5G - Small Cells 'Steal the Thunder' in 5G Era

Author: Balaji Thangavelu, Principal Consultant, Engineering Services


In this blog post, I have shared my thoughts on the significance of small cells in 5G, and how we need to gear up our innovation capabilities to address some unique challenges associated with small cell infrastructure deployment and RF planning.


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November 12, 2018

IIoT - Industrial Internetization - Impact on Organizational Structures

From Internetization of people, we have gradually moved towards Internetization of industry. For an industry, organization itself and its competition, both are in a state of flux, and getting reshaped dramatically with the evolution of IIoT Ecosystem. As an outcome of converting non-living products into intelligent, connected and communicating smart devices, a not so envisaged scenario of transformation of organizational and operational structure has automatically started. Organizational structures built over previous three industrial revolutions, have started crumbling with the dawn of 4th Industrial revolution. 

While change has been a norm across all organizations, manufacturing industry has received most lethal hit till date. As Jeff Immelt (GE CEO) pointed out way back that every industrial company must become a software company, and rightly so, massive transformation across manufacturing companies have already begun. Without focusing on external implications (Strategy, Competition, Industry structure and Industry Boundary) which the world of IIoT is bringing in the world of Industry, an observation of internal implications for an Industrial organizations bring following pattern very visible - 


 1. Classical model of manufacturing company being divided into departments like R&D, manufacturing, sales, marketing, finance & IT would give into new models where practice of periodic hands-off across departments would be replaced by continuous co-ordination across functions.

2. As a result of products becoming intelligent, relationship between organization with its products and its customers is becoming continuous and open ended now.

3. Data would drive decisions in place of whims and fancies of individuals.

4. Traditional centralized model of command & control of management would be challenged by rich data and real time feedback. 

       

       There are number of below mentioned noteworthy shifts providing enough indications on how the industrial companies would evolve and how their organizational structure would go through massive changes -

  1. IIoT driving pervasiveness of IT - IT has already started assuming more central role in R&D or Engineering activities which has been the work of core R&D department till now. With the need to embed IT hardware and software in the product itself to make it smart, IT has become pivotal to R&D activities. Only time will tell if we shall continue to have R&D and IT as two separate departments or one would be made responsible for other or vice versa. Truth is, need to create smart and communicating product has ensured that there will hardly be any R&D without IT anymore.
  2.  Industrial Dev-Ops - With product becoming intelligent and connected, there is a continuous feedback loop which has come into existence with products relaying all the key information to its creators. In order to understand, manage and drive value out of this communication loop, similar to Dev-Ops model of IT, Industrial companies are exploring collaboration mechanism between teams responsible for product development and product support/operations. Aim is to reduce product release cycle, to provide better customer services and to get and understand the actual on ground feedback on products through IIoT ecosystem. Concept of Digital Thread is a step in this direction only.
  3.  Data Organization - Data is the new oil of the economy and same holds true for and industrial company as well. With millions of sensors, IIoT ecosystem generating data at enormous speed and scale, getting strategic value out of the data would remain a big challenge. In view of this, there would be an effort towards creation of data specific entity responsible for collection, consolidation, analysis and bringing in the insight aspects of right data. Appointment of Chief Data Officer across organizations is a baby step in that direction itself.
  4.  Consumer Management - Smart connected products through IIoT ecosystem has the capability to drive and deliver the value in PAAS (Product as a Service) model. It would be imperative to monitor product usage and performance data to understand the value being provided to consumer and mechanism to improve this further. Traditional sales & service teams are not equipped to cater to this changing scenario. Would there be a separate group responsible for managing consumer relationship in the world of IIoT? Only time shall answer this question.

 

For an Industrial organization, it is a journey from 'here' to 'there'. Organizational structures efficiently catering to the world of IIoT are yet to come. Changes are huge, while skills are very limited. Whether the structure would involve setting up separate business units, or to answer the change through amalgamated cross functional mechanism, or through COE routes, organizational structures will change for sure.

In this new world of IIoT, things have started speaking between themselves, and, with us as well. Very often, things speak softly, but at times, so loudly that it is not only organizational structure which will be shaken to the core, it is possibly our societal structure itself which may start reshaping someday, because, IIoT is not an evolution, but a revolution. 

September 7, 2018

Address condition monitoring and predictive maintenance challenges in the Aerospace Industry with Krti 4.0

Let's begin this blog post with a story. A man wanted to learn how to swim. He began by speaking to a few people about it and reading a few books on swimming techniques before heading to the lake. But, there began his problem: While he practiced the motions and went through every movement and stroke he had read about and discussed, he was still unable to keep his body afloat. Frustrated, he looked around and saw a person enjoying a leisurely swim in the middle of the lake. He waited for the swimmer to come ashore and asked if he could teach him how to swim. Soon, with a few lessons, the man was swimming by himself in the lake.

 

The message of the story is: It is easier to learn from a practitioner than a theoretician. This approach applies to almost every scenario that requires individual knowledge coupled with the guidance of someone who has traversed the path to successfully accomplish something. Now, swimming may be a simple skill to learn and, in the story, the investments needed were time and money spent on a few interactions and purchasing the right books. But what if an enterprise wanted to enhance its operational efficiency at an organization level? Here, the investments would be much higher and the ROI would need to be well-defined.

 

Take the example of aerospace and defense, a technology and investment-intensive industry burdened by strict safety and regulatory requirements. This industry needs stringent quality and production measures for consistency, reliability and high performance. The success drivers for organizations in this industry are high product quality and operational efficiency. From a theoretical point of view, the following levers can help organizations achieve manufacturing and operational efficiencies:

 

  • Intelligent management of critical shop-floor assets such as time-sensitive raw-materials, kits, molds, tools, and the workforce
  • Sophisticated algorithms powered by AI and data analytics that suggest next steps by sending out context-aware alerts and recommendations

 

Much like the earlier story about swimming, these levers look great on paper. But, without alignment with a practitioner's perspective, these may be insufficient to achieve the desired goals. So, how does one find the practitioner's view? This is possible by accessing processes and frameworks developed by organizations that have already deployed reliable systems with assured performance along with data prediction and connectivity between assets to collect data. In fact, I think that could actually mean the difference between the success and failure of any transformation program.

 

Condition monitoring and predictive maintenance - A practitioner's view

 

KRTI 4.0 is an AI-based operational efficiency framework developed by Infosys and Pöyry by leveraging decades of industry experience working with global organizations. This framework enables aerospace OEMs and Tier 1 suppliers to deploy a system that significantly enhances the reliability of operations and maintenance on the manufacturing shop floor. The KRTI 4.0 framework is unique because it leverages the different expertise areas and key operational experience of Infosys and Pöyry to provide a practitioner's view:

 

  • Pöyry specializes in reliability, availability, maintainability, and safety (RAMS) modeling and engineering design for different industrial processes. Its dynamic RAMS models are based on effective use of Industry 4.0 technology and backed by intense field knowledge of asset behavior
  • Infosys leverages its rich engineering experience gained by working with different aerospace OEMs as well as its knowledge of manufacturing practices to create knowledge, operational and maintenance models coupled with data analytics and AI-based resolutions. These models form the backbone of the KRTI 4.0 framework, providing condition-based and predictive maintenance at the shop floor level rather than at an individual system level.

 

As a framework, KRTI 4.0 differentiates itself from other condition monitoring and predictive maintenance solutions by offering a comprehensive shop floor-centric view based on reliability rather focusing on asset availability. This unique capability enables OEMs to schedule maintenance, resources and inventory based on reliability assessments. Moreover, decision makers gain a 360-degree view of risks associated with anomalies in terms of business, human and environmental safety.

 

Connect with us to get real-world guidance on how to improve the operational efficiency of your organization. 

September 6, 2018

Krti 4.0: Reasserting the Relevance of Knowledge Modeling

Seamless knowledge management is a problem that many organizations grapple with. Consider how, in traditional engineering, knowledge about industrial systems and processes often reside within software code and documents, and with domain specialists. Many times, such knowledge is lost when domain specialists retire or are redeployed or when software applications are upgraded or replaced. Software migration itself poses significant technical challenges as it is often difficult to understand the logic of knowledge embedded in software applications. Further, documents describing business logic are sometimes not updated, resulting in incomplete capture and processing of business knowledge.

I strongly feel that problems related to the loss of critical business knowledge can be easily alleviated by capturing, representing and processing such knowledge in a manner where the lifecycle of the product and process is properly managed. This is where intelligent knowledge modeling comes in.


Breaking down knowledge modeling

Simply put, an ontology is a set of object types, objects and relationships as well as the attributes of objects and relationships. Knowledge models based on ontology structures can theoretically capture, represent and process infinite amounts of data associated with a system by using objects, relationships and attributes. An ontology representation can also deterministically connect the ontologies with external systems such as databases and downstream systems in order to take relevant actions.


Here is an illustration of a knowledge meta-model:

 

blog_metamodel_1.png

Here is another illustration of a knowledge model that is an instantiation of the above meta model:

blog_model_1.png

When knowledge is managed using such models, it greatly enhances product development by accelerating the design and development of new and similar products from existing designs.

Knowledge models can also be used to improve the problem-cause-resolution process in maintenance and operations. The illustration below demonstrates how this can be done:

 


fig22_ccn_blog_sep2018.png

Solve business problems with comprehensive knowledge modeling

Infosys and Pöyry have collaborated to create KRTI 4.0, an industrial solution to help companies capture and represent embedded knowledge around problems, symptoms, root causes, and resolutions. The KRTI 4.0 framework uses knowledge models to provide a host of tools such as dashboards, graphs and alerts for clear problem resolution lifecycles. These help users such as plant managers, supervisors and technicians to understand and interpret both static and real-time aspects of the system. These knowledge models are particularly useful for enterprises in the power, oil and gas, paper, and automotive industries that must capture knowledge across multiple plants and data across multiple systems to gain insights about problem identification and resolution.

Learn more about how KRTI 4.0 can help your organization capture knowledge to solve business problems faster.

 


August 7, 2018

Creating a Peer-To-Peer Connected World of Cars with Blockchain and IoT Synergy

 

Leading automotive giant, Toyota recently announced the development of a slew of proof of concepts on IoT and blockchain synergy. Toyota has leveraged blockchain technologies such as smart contracts, Ethereum based distributed ledgers, and data from IoT sensors in these proof of concepts.

By doing research and creating PoCs, Toyota and other original equipment manufacturers have developed ecosystems in which end consumers and enterprises can perform a number of functions in a secure manner. These include,


•Management of peer-to-peer ride sharing and car sharing transactions

•Storage of information on vehicle usage, which can be used in usage-based insurance

•Sharing of driving data to map road and traffic conditions

In this blog post, we discuss peer-to-peer ride and car sharing.

A car ride or share transactions is a use case to monetize cars by selling or sharing rides, and cargo space. It also includes leasing out of vehicles on a peer-to-peer basis without a centralized authority, such as a vehicle aggregator or rental agency.

This can be done by leveraging the advances in blockchain and IoT, and these advances have the potential to disrupt established players and replace their central trust systems with a blockchain-based distributed ledger and de-centralized systems.

Continue reading "Creating a Peer-To-Peer Connected World of Cars with Blockchain and IoT Synergy " »

July 26, 2018

Digital Transformation - Where are we headed?

Continue reading "Digital Transformation - Where are we headed?" »

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