With more than 25 years of or work experience in power plant control systems and automation domains, Todd Ashley is currently serving as the VP of Digital and Industrial solutions at QuEST Global, a firm that provides comprehensive digital solutions across the life cycle — from new product introduction to manufacturing. In his current role, he directs strategy, execution and growth for digital solutions that enhance business value and create new outcomes for customers.
Analytics India Magazine got in touch with Ashley who has previously worked with companies like GE in the past. In this interaction he shares the role of QuEST in analytics space, developments in areas such as augmented reality, virtual reality and their growth plan, among other things.
Analytics India Magazine: QuEST Global is quite prominent in areas like IIoT and automation. Please tell us in detail about the solutions provided by your company.
Todd Ashley: For more than 20 years, we have been providing comprehensive solutions across product life cycle of world’s recognised Fortune 500 brands in aerospace, defence, aero engines, transportation, medical devices, and others. From deep learning capabilities to cloud development, big data analytics, mobility and user experience, QuEST provides solutions and outcomes that matter across the Industrial IoT spectrum. We also offer market leading pervasive technologies in the areas of augmented/mixed/virtual reality, artificial intelligence, deep learning, security and blockchain.
Through QuEST’s Digital Center of Excellence (CoE), customers can benefit from a range of flexible business models that enable cost optimisation through local-global managed services. This is accomplished with focused Delivery leadership, lab infrastructure, software platforms, accelerators and partnership with third-party technology providers such as Microsoft, Google and NVIDIA.
AIM: Please explain QuEST’s role in analytics space.
TA: QuEST plays a strategic role in the engineering analytics space. For us, engineering analytics is a core of digital experience that not only helps in the product development process but also enhances user experience.
We offer big data and analytics services in data integration and legacy migration, Hadoop services, business intelligence and reporting. We have active engagements in classic analytics like processing fleet data, trending/regression, and taking design actions to mitigate or reverse trends. We also have cutting edge engagements where we apply deep learning to data sets to enable new outcomes and more proactive and predictive solutions. Our product experience and expertise offer us a unique capability to act and engineer solutions-based on analytics.
AIM: What industries do you cater to?
TA: QuEST has analytics engagements in key high-tech and industrial verticals. An exciting high-tech project we are working is an analytics app for Android and Windows 10 platforms that provides a comprehensive overview of device health and performance. Through proactive and predictive reporting, the app identifies and prevents issues before product release to consumers.
We also have analytics projects in oil and gas, power, transportation, and aero engine. For instance, we do remote monitoring, diagnostics and analytics to assess the health condition of customer and end customers assets (both online and offline). We also predict and prevent any potential failures of the assets to reduce the operational downtime, thereby enabling scheduled and hassle-free maintenance activity.
AIM: Tell us about digital manufacturing how will it improve manufacturing processes and what QuEST is doing in this area.
TA: As the primary vehicle for companies to transition to Industry 4.0, digital manufacturing involves the application of technology to the entire manufacturing value chain, ultimately resulting in greater productivity, reduced costs and higher quality output. To ensure successful implementation of the latest technologies to the manufacturing process, it is important for companies to work with a strategic and experienced partner who can overcome challenges in the digital transformation journey while minimising the impact to employees and day-to-day production.
As a pioneer in delivering customised digital solutions, QuEST’s approach involves combining tangible engineering benefits with management improvements to throw light on future disconnects in the factory and supply chain. We sync our process management knowledge and product engineering skills to accelerate the pace and accuracy with which customers migrate to 3D models, adopt model-based design and consumption, engage with design for manufacturing and flexible manufacturing.
Last year, we began our collaboration with Siemens AG to offer a complete suite of connected manufacturing services across verticals. We are a development partner with Siemens for their PLM solutions and have an innovation lab to design and test new solutions.
AIM: How is it helping organisations in real-time data and predictive analytics? Please explain with a use case.
TA: Big data and advanced analytics solutions such as condition-based maintenance and predictive maintenance represent a great opportunity to yield the next big efficiency leap in maintenance – reducing the number of failures, the amount of unplanned maintenance and, eventually, achieve the required level of reserve asset capacity for industrial equipment operators.
QuEST’s Analytics Response Center (ARC) assesses parts capacity, availability, and demand, as well as predict issues that may impact fulfilment, so that action can be taken in advance. We also have an analytics-driven IoT Asset Tracking Platform that can provide broader visibility by incorporating factory, supply chain, location, and inventory margins.
As an example, various studies in Power and O&G domain show a significant production loss and operating cost occur due to unscheduled refinery shutdowns. To reduce unplanned shutdowns, QuEST has developed a joint solution with a customer to monitor real-time performance of assets in refinery and predict maintenance requirements.
AIM: How is the company using analytics internally?
TA: We utilise our data and analytics capabilities to generate operational measurements automatically that drive quicker review and decision making. We also “incubate” and invest in new ideas in high demand pervasive technologies like Deep Learning to prove concepts on new potential outcomes for our customers. For example, in the Deep Learning space, we are researching improvement of soft tissue anomaly detection and discovery of pipeline defects.
AIM: What is the company doing in the area of virtual and augmented reality?
TA: AR360 is our platform to easily deploy and manage AR/VR solutions. We provide content development and management in 3D modelling, animation, interaction definition, image content and publishing services for tablets, smartphones, HoloLens, SmartGlass, and Google Glass. We also offer enterprise integration with authentication, authorisation, content and workflows. AR360 is active in the manufacturing space, healthcare, telecom, and Oil and Gas.
For instance, one of India’s leading manufacturing companies for industrial machinery was finding it increasingly difficult to create an immersive training experience for the maintenance module of their complex machinery. They were unable to show hidden parts of their machinery even during field training. Additionally, there was no way for trainees to self-study and rehearse the machine operations remotely. QuEST implemented an Augmented Reality solution that runs on Microsoft HoloLens and offers a hands-free experience. It provides complete visibility of the actual machinery with the help of 3D content and the interaction with training content takes place through hand gestures. The solution eliminates the dependency on field machine to understand the detailed parts of operation. Even when on the field, with features such as Remote Assistance, help is just a gesture away.
AIM: Is the company focusing on technologies like artificial intelligence and machine learning?
TA: Yes, we are focusing on technologies to proactively address industry demand in artificial intelligence such as Deep Learning and Machine Learning. We have a team of experts in with skill sets in training, validation, deployment of Deep Learning networks as well as experience in multiple computing frameworks and processors.
QuEST was the first company worldwide to be selected for the NVIDIA Deep Learning Consulting Partnership Program. Combined with our big data capability we have a host of projects and active engagements across automotive, finance/insurance, healthcare, smart city, industrial IoT in the image detection, natural language and sensor data processing. We specialise in tackling data with our Deep Learning innovation approach and exult in finding outcomes that were only imagined previously.
AIM: How has been your growth story?
TA: We have seen tremendous growth over the years in terms of technology and have enjoyed organic growth in our industrial and hi-tech verticals. Driven by our customer requirements, we are continuing to invest in digital services capabilities to enable faster digital transformation for our customers in engineering and services. In the recent past, QuEST has acquired Mobiliya, Exilant, IT Six and engicom, which brings a host of capabilities and platforms related to IoT, AI, augmented reality, blockchain and cyber security. We are successful in developing multiple digital solutions, which are built on top of our platforms such as Asset Tracking and Fleet Management and Augmented Reality.
AIM: What are the challenges you face?
TA: Our biggest challenge is the high demand. We are fortunate to have the good problem of increasing demand and the challenges associated with increasing the speed of delivery and engagements. We are proud of our capabilities but remain humble as we approach new and existing challenges and are constantly looking for better ways to provide outcomes that matter.
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Srishti currently works as Associate Editor for Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.