In the digital era, businesses are striving to deploy high-quality experiences faster to succeed. The acceleration of technology innovation and the aspiration to adopt digital business models present challenges for organizations to meet their business needs. Managing multicloud environments has been a significant challenge for many customers due to different consoles, teams, and skills required to realize the benefits of these clouds. Business leaders are mandating their IT departments to consolidate IT infrastructure to save energy costs, host more applications, share resources across different departments, and enhance security. These requirements often translate into fewer data centers and consolidated server, networking, and storage resources that can host multiple applications shared by multiple departments.

The challenge was to harvest and sift through this data, recognize the patterns that indicate a high likelihood of asset failure, identify the most urgent issues, and get the right information to its engineers with enough lead time for them to take effective action.“Before, we only used between 10 and 12 percent of the operational data we collected, which is the industry average,” comments Benn. “By the time we had searched for, collated and forwarded the right information to the right people, we might respond too late to avoid impact to operations, or have to make last-minute changes to our maintenance schedule, which reduces efficiency. Our challenge was to provide right-time, actionable, effective information proactively, rather than in a reactive or look-back assessment.”“What we wanted was a way to identify patterns in that sensor data that would give us an early warning of asset failure. We saw an opportunity to use analytics technology to extract greater value from the systems and data we already possessed, which would help us to, for example, avoid preventable failures and potentially save millions of dollars.

Based in Bolton, England, Ascribe is a leading provider of business intelligence (BI) and clinically focused IT solutions and services for the healthcare industry. Ascribe estimates that 82 percent of National Health Service (NHS) trusts in the United Kingdom use its products. With access to large volumes of data maintained by the trusts, the company wanted a BI solution that would help healthcare providers detect, predict, and respond more quickly to outbreaks of infectious disease and other health threats. Healthcare analysts typically work from data collected and coded when patients receive treatment in clinics and hospitals. “By the time they get that information it’s usually out-of-date,” says Paul Henderson, Business Intelligence Division Head at Ascribe. “The data has already been coded and stored in a record-keeping system, or it’s been collected from a hospital workflow, and that doesn’t always happen in real time.” In addition, huge volumes of potentially useful data existed in text files from sources such as unscheduled visits to emergency rooms, school attendance logs, and retail drug sales. The Internet offered another trove of untapped information including clickstream analysis and social media such as Twitter. “If you think about each clinician who struggles with getting timely, accurate data, and you compound it on a national scale, then it becomes an immense challenge,” says Henderson. “You have lots of small pieces of data coming in from multiple places, and it can be very difficult to aggregate and interpret.”Ascribe had previously worked on a solution to support the analysis of national emergency care attendance. The system was designed to monitor the daily number of people who visited emergency departments in the UK and raise an alarm when it identified unusual levels of activity such as a potential outbreak of an infectious disease. However, it was difficult to collect data from a rapidly growing number of healthcare providers, including mobile clinicians. In addition, clinicians were unable to use the exploding volume of unstructured data from patient case notes and social media feeds. “The processing power you would need to handle all of that information is beyond the capability of most organizations,” says Henderson. “A hospital can’t just stand up a server farm to process millions of case notes from an emergency care system in addition to other data.” To solve these problems, Ascribe decided to design a proof of concept that would create a standardized approach to working with healthcare data. The company asked Leeds Teaching Hospitals, one of the biggest NHS trusts in the UK, to participate in the project. Leeds can generate up to half a million structured records each year in its Emergency Department system. The hospital also generates approximately 1 million unstructured case files each month.Ascribe wanted to create not just a proof-of-concept BI solution for monitoring infectious disease on the national level, but also a tool that could be used to improve operations for local care providers. “Our goal was to find a way to make data flow more quickly in near-real time,” says Henderson. “We also wanted to augment clinically coded data with data harvested from case notes.” The company wanted to create a national knowledge base that both analysts following disease outbreaks and local clinicians could use to improve healthcare. Ascribe needed a highly scalable, end-to-end solution that could work with multiple data types and sources, as well as provide self-service BI tools for users.

University of Udine is a college committed to the highest education standards, research, interaction with surrounding territories. The collaboration with Endian brought its technological vocation beyond the academic field to translate into a project aimed to protect and safely manage accesses to electrical and thermal control systems, access control and video surveillance.

Security Watch or Cam Pack is the surveillance App/Device that turns your iPhone into an instant spy. Use the Bluetooth Camera Device to stream live what’s happening behind you. Perfect for situations when you feel the person is suspicious or ready to rob/assault you from behind. The device is worn like a watch on your wrist. The device captures the video and transmits it to the Mobile App through Bluetooth. The App takes care of the rest. The app has a panic button that calls to 911 immediately in case of any danger.

This property management company needed accurate waste reporting to meet sustainability certification standards, but their previous waste provider could only provide general estimates. 

Sean Simon is the SVP of Operations at CIG Logistics, where sand is transloaded and stored for third parties in the oil and gas industry. Before looking into CMMS solutions, his team spent three years trying to manage their maintenance operations with a paper-based system, leaving them with the major issue of not being able to gather or access data. “There’s no way to mine paper. There was no daily summary, no way of tying together comments or keywords.” As a result, trying to track and schedule preventive maintenance was nearly impossible. “It was like owning a car in the 1950s. You had to try to remember the last time you did something and guess at the maintenance that needed to be done in the future”.

Allowing defects to escape the factory damages customer relations and the brand, and leads to costly rejects or returns, while overcontrolling for defects internally leads to high labor, scrap, and rework costs. The pernicious problem of defect detection was supposed to be solved by machine vision inspection, but in many instances machine vision systems are not up to the task.No condition monitoring on valves & motors.Root cause analysis on failed equipment was difficult or nonexistent.Engineers spend hours per week producing spreadsheets and analytics.

Due to declining workforces in ageing societies such as Japan, securing sufficient human resources is becoming increasingly difficult, which in turn is raising the demand for AI that can support efficient mechanized operations. New production facilities, however, present special challenges due to differences in pre-learned and actual shop environments, resulting in huge amounts of time devoted to teaching AI before it can be implemented on a full scale.

In 2019, a global leader in electronic instrument manufacturing aimed to improve their organizational shortage communication and achieve ambitious inventory reduction goals. The company's demand varied from item to item, which complicated their inventory purchasing process and affected supply to the manufacturing floor. This put factories at risk of production-halting critical shortages. The management of this complexity was challenged by an unwieldy ERP system and a lack of total visibility into operations. Establishing optimal order policies for inventory management was possible in the ERP, but it required manual ABC analyses, a cumbersome process that took three to six months. The team viewed these analyses at a quarterly cadence, arguably too infrequently to react to market demand. Metrics around action items, time management, usage, and average demand were not available to the team in their ERP system.

AdventHealth Orlando, one of the busiest hospitals in the U.S., faced significant security challenges. Despite having a well-trained security staff, the hospital needed additional surveillance to monitor activities that could not be covered by human personnel alone. This was particularly crucial in situations where a person was quickly dropped off at the emergency room by a driver who then left the scene. The hospital staff found it challenging to document such incidents and identify the driver reliably. Additionally, the hospital required real-time analysis of traffic entering and leaving the premises to understand parking usage by staff and patients at different times of the day. This data was critical for the efficient operation of the hospital and future growth planning. Lastly, the hospital needed a secure automatic access control system for its staff garage. The existing methods required excessive human intervention and failed to prevent non-staff from parking in the garage.

Tsingtao Brewery, a 116-year-old Chinese brand with over 60 breweries across the country, faced the challenge of maintaining its rich heritage while keeping pace with intensified market competition. The brewery's IT infrastructure, a critical platform for its operations, was in need of a more scalable, flexible solution to support new business initiatives. As part of an ongoing effort to improve product quality, service, management, and create more value for consumers, Tsingtao Brewery launched an initiative to upgrade its core business operations and support an intelligent new retail model. The digital transformation of its IT infrastructure was a cornerstone of this strategy. The brewery needed an agile, scalable data center solution that would meet its strict technical and operational standards.

Smart Wires, a Silicon Valley-based developer of grid-optimized solutions, faced several challenges in its mission to transform how power grids are operated worldwide. The energy market was grappling with an aging, inefficient electrical grid prone to bottlenecks, and a growing demand for renewable energy sources. This situation was further complicated by the need to deliver products affordably amidst cost pressures. Smart Wires also needed a strong supply chain partner with a global reach to compete with large, multinational competitors. Their highly complex products required manufacturing collaboration and processes to expedite innovation while meeting rigorous safety and reliability requirements.

Unistar LC, a leading ICT provider in Slovenia, was facing a challenge in facilitating customer access to the cloud. The company had developed more than 10 brands, including Unistar PRO.cloud for hosted and managed IT services, but needed a scalable, cost-efficient, and reliable platform to enhance this offering. Despite being a NetApp partner for over a decade, Unistar LC was uncertain about choosing NetApp solutions. The company needed to ensure that the chosen solution would provide the best value for money, a quick return on investment, and compliance with Slovenia’s strict data protection regulation. Additionally, Slovenia's data protection laws do not allow personal data to leave the European Union or even the country in some cases, which ruled out the option of connecting to an Amazon or a Microsoft cloud.

Most organisations apply a “Reactive Maintenance” approach to their processes, in which repairs and replacements are made to the equipment after a failure occurs. It costs around 10x more to repair a machine after it fails, not to mention the direct impact on revenue and customer satisfaction. Through “Preventative Maintenance” equipment is repaired or replaced at pre-set time intervals in order to avoid failure. Whilst this approach reduces unplanned downtime it is expensive as these scheduled repairs take place when there can be nothing wrong with the equipment. However, the benefits of predictive maintenance are significant, so it is becoming the preferred method for manufacturers, enabling organisations to foresee and schedule repairs and replacements when needed, achieving 100% operational uptime of the equipment.  One challenge for traditional machine learning in manufacturing is that techniques require clean and complete data. However, manufacturing and process data can be sparse and noisy.Currently, it is difficult for engineers to access and interpret production process data, they rely on personal experiences and opinions to modify process parameters. This leads to inconsistent and potentially suboptimal decision making, and moreover increases the risk of process failure, increasing associated time and costs. The production line is especially difficult to model using standard techniques due to the inherent time lag and inertia between changing operating parameters and their effect. Costs associated with waste materials and failed production could also be significantly reduced with the application of relevant and innovative deep learning technology to design production processes more efficiently.

CVC Technologies, a leading manufacturer of pharmaceutical packaging machines, was seeking an end-to-end IoT solution to fully digitize their pharmaceutical liquid filling and capping machines. The company aimed to enhance the safety of their equipment, introduce digital maintenance capabilities, and gain visibility into machine status from anywhere at any time. The challenge was to find a solution that could provide real-time visibility into the machine's status, deliver direct cloud connectivity and digital services, and simplify all aspects of the machine's lifecycle, from engineering to maintenance.

Deutsche Telekom, a global leader in Machine-to-Machine (M2M) and Internet of Things (IoT) communications, was faced with the challenge of quickly establishing a presence in the fast-paced IoT market. The company needed to find a technology partner that could provide a fully rebrandable platform to launch a solution that could get customers up and running in minutes. Deutsche Telekom recognized that its enterprise customers, including Dürkopp Adler, Deutsche Afrika Linien, HUBTEX, and Definitiv, needed to transform their businesses to remain globally competitive and innovative. The company aimed to simplify IoT adoption and enable its enterprise customers to efficiently implement end-to-end IoT solutions. This would allow these businesses to increase end-customer service levels and customer satisfaction, lower operational costs, and transition from product-centric to service-centric companies.

Emerson's old address verification systems couldn't handle language barriers and non-standardized address formats, which proved to be a major obstacle in dealing with international address validation. Emerson needed an address verification system that would cover their expansive list of countries and native character sets, provide superior customer support and be simple and cost-effective to implement and manage.

Matto Central Hospital in Hakusan, Japan, established in 1948, was facing a significant challenge in training its physicians on new robotic surgery techniques for prostatectomy and other procedures. The hospital had recently acquired the da Vinci robotic surgery equipment, which required hands-on training and experience. However, being a relatively small hospital, finding the budget for a simulation lab was a significant hurdle. Despite the financial constraints, the hospital recognized the importance of a robotic skills lab, especially for the surgical residents who found it attractive.

Pulaski Bank, a customer-centric financial institution, was facing challenges in tracking and resolving issues that arose during the pre-close, pre-shipping, or suspense load processes. The bank had phased out its existing issue tracking system and was in need of a new, efficient system that would provide visibility and ownership to each issue, ensuring timely resolution. The bank required a system that was tailored to their specific needs and could streamline the process of issue tracking and resolution. The absence of an efficient system was potentially affecting the bank's customer service and overall operational efficiency.

TCS has partnered with ABN AMRO bank to explore the potential of blockchain in the clearing and settlement segment. This test explores how tokenized cash balances and equities are allotted and transferred between issuers, clearing banks, and investors. We leveraged our PoC platform within a sandbox environment integrated to their back-office platform. This engagement tries to establish whether a distributed ledger integrated with legacy systems can create a‘single source’of truth to allow instant cash settlements

The Royal Victoria’s 20-year-old Mitel system, with separate analogue voicemail system, needed to be replaced. The hotel required a modern communications solution that would:Connect the hotel's 160 employees.Provide call logging to help monitor business performance and control costs.Provide communications to mobile members of the team such as the night porters.Improve guest WiFi internet access.

Solebit (MimeCast), a company that provides identification and prevention of zero-day malware and unknown threats, was facing significant challenges with their testing processes. The existing automation tests, designed and developed by the in-house team, were not efficient. The tests were manually triggered by developers in a terminal, resulting in a large and complex file of results. The tests took over 20 hours to complete, and there was no history of the test runs available. The architecture of the test suite was unscalable, making it difficult to maintain a large number of test machines. The challenge was to create a simple runner for tests, increase their speed, redesign the architecture to support cloud platform integration, make the tests run more easily, and generate a clean report with all the necessary details. Additionally, improvements were needed for the current testing process, and some manual testing was also required.

The Driver and Vehicle Standards Agency (DVSA), an executive agency of the UK government, was facing a significant challenge in its digital transformation journey. The agency was transitioning away from long-term contracts, minimizing vendor lock-in, and moving towards open source and cloud solutions. This shift was aimed at improving efficiency, adding flexibility, and gaining value for money. However, the agency was encountering issues with its connectivity. DVSA was connecting to the cloud via virtual private networks (VPNs), but the VPN firewall ran out of capacity, necessitating an alternative solution. The challenge was to find a solution that would provide fast, reliable connectivity, essential for the agency's digital transformation.

The European Space Agency's Research and Service Support (ESA RSS) is a service that provides resources to support Earth Observation data exploitation. The main purpose of the RSS service is to provide its customers, who are primarily researchers from universities and research centers, service providers, public institutions, and medium-sized enterprises, with reliable and performant services. The challenge was managing the variable workload and the diversity of processing required. They needed a solution that would allow them to focus on their main responsibilities, specifically in terms of development and support, without being distracted by basic operational requirements.

The client was in the process of developing a smart table tennis robot that can be controlled by a mobile app. The app can be used by players to configure or choose from a list of pre-programmed drills. The robot plays the drills and programs as per user configuration; however, performance reduces over time due to aspects such as the wear and tear of machine parts. Additionally, faulty installation, errors in table dimensions, and alignment changes caused during shipping impact accuracy.QBurst was tasked with improving firmware performance. The project would focus on enhancements to the calibration mechanism of robots leading to improved gameplay and user satisfaction. The client wanted the calibration mechanism to be easy to use and repeatable.

The piston's compression ring serves several functions in a reciprocating engine, including sealing the combustion chamber and regulating fuel consumption. Defects on the compression ring are difficult to detect due to the reflective metal surface of the piston. The cylindrical shape of the piston is sometimes blurred and out of focus in the image. Normal variations in metal surface texture are expected as part of the manufacturing process, and some of these variations are acceptable, including rust spots, white areas, and surface cracks and fissures. But some long scratches that affect piston performance and threaten compression levels in the cylinder are the real flaws. The inspection system must be able to ignore normal variations and insignificant anomalies on the compression ring surface while identifying longer scratch defects.To program such complex inspections to rule-based algorithms would require complex defect databases. While manual detection is more flexible, it is too slow.

Helping Small Businesses Overcome Big ThreatsThe majority of CDK’s customers are small in size and consequently may not have the resources, personnel, or expertise to comprehensively protect their networks.

Diversified Funding, Inc. (DFI) recently purchased the Apartments at Remington Pond in West Warwick, Rhode Island, and embarked on a major renovation project, including the installation of new Fire Alarm Systems in each of the seven buildings. The challenge for DFI was to ensure that the apartment building met the latest fire alarm codes, including the new sleeping room requirements listed in both the National Fire Protection Association (NFPA) 72 National Fire Alarm and Signaling Code and the NFPA 720 Standard for Installation Carbon Monoxide (CO) Detection and Warning Equipment. These codes require that audible appliances in sleeping areas produce different low frequency alarm signals - T3 for fire and T4 for Carbon Monoxide (CO) detection. To meet these requirements, DFI hired PowerComm Systems, a leading fire alarm and security provider in Rhode Island.

Lippuner has nearly 350 employees across four cities. Each employee orders new phones every two years. Their marketing department generates about 450 orders per year across 41 different items—for a total of 18,450 orders. In the past, these orders were processed using paper forms, causing slowdowns and adding time to the process. These outdated processes didn’t comply with the company’s high standards of efficiency.