The UK-based instruments engineering company was facing challenges with their existing system of capturing, managing, and analyzing data from live machines and systems. The sensors installed on various components of industrial equipment like turbines and pumps captured physical data at a high frequency, which was then managed and analyzed locally on desktop-based systems. This resulted in manual, inaccurate, and time-consuming fault detection. The company decided to automate data collection, enable cloud-based data processing, and implement AI-based fault detection. However, they faced several challenges including the difficulty of scaling and deploying traditional predictive tools, the need for predictive analytics to be embedded within their application, the requirement of expertise for data preparation, cleansing, choosing the right algorithm, training, and validation, and the need for the platform and application to easily integrate with all hardware products.

The U.S. manufacturer of engineered materials, optoelectronic components, and semiconductors was focused on growth through mergers and acquisitions (M&As). In 2019–2020, it acquired a global electronics firm and needed immediate connectivity and visibility into the acquired firm’s geo-distributed operations. The company had a highly compressed timeline, with only days to integrate the firm’s DDI operations, while deferring a full network migration to a future date. The company was actively engaged in acquiring and merging strategically aligned companies as a key global growth strategy. The company needed to rapidly integrate its new operations, which included significant remote locations in Asia. The company turned to Infoblox to quickly design a highly secure, available, and reliable solution that could deliver full visibility into new sites. It needed dynamic scalability to accommodate its growing operations and the ability to unify a disparate, geo-diverse infrastructure.

To deliver the first environmentally sustainable smart city as the new capital of Chhattisgarh state.To use optimized solutions to meet the needs of citizens and businesses.To enhance quality of life through safe, efficient, sustainable civic amenities and planning systems.

National Instruments was concerned about the future state of its enterprise search solution. Microsoft’s FAST ESP was no longer offered as a stand-alone product and it was marked for end-of-life, effective July 2013.

Aramex, a global leader in the logistics and transportation industry, was facing challenges in staffing their fast-paced, innovative projects locally. They were in need of a technology partner who could not only support their digital strategy but also contribute proactively to design and ideation. Aramex's business model is 'asset-light' and they place a high emphasis on technology and innovation as key differentiators and growth enablers. However, the innovative and user-centric nature of their projects required extensive expertise in data science, UX design, business analysis, and R&D, which they were struggling to find locally. In late 2015, Aramex decided to look for a technology partner from Eastern Europe to support their entire delivery process.

The client wanted to reduce downtime and production losses by effectively prioritizing maintenance activities and proactively replacing components before failure.

In late 2015, a deployed combustion turbine experienced a row two vane failure, which caused massive secondary damage to the compressor, resulting in nearly two months of downtime and up to $30M in repairs costs and lost opportunity. This failure, though rare, is representative of typical catastrophic events that are very difficult to catch. Though the onsite plant operations team had been monitoring the asset, this specific failure mode was previously unknown and very nuanced, and existing alarms did not have enough information for SMEs to properly diagnose it in time.The OEM decided to evaluate SparkCognition’s predictive analytics solution, SparkPredict®, with the following objectives:1. Demonstrate the ability to detect and distinguish operational and anomalous online steady-state conditions based on blind data provided from the turbine.2. Provide additional insights about the key contributing factors to the underlying anomalies.3. Provide a UI that interfaces to live streaming data from the asset.

The ROTHENBERGER Group, a world-leading pipe tool and pipe machining tool manufacturer, was facing challenges in monitoring their assets. They were using traditional tower lights and 24V controls provided by the machine vendors, which did not offer accurate visibility and full transparency into the production floor. As part of their transition to the industry 4.0 era, ROTHENBERGER was seeking a solution that would provide reliable and trustworthy visibility into their production processes. They needed a system that could provide real-time status of machine availability across their factories and highlight major gaps in productivity. The goal was to address and resolve these gaps through data-driven decision making.

Vital Energy, a leading energy company, was seeking ways to increase productivity, lower production costs, avoid downtime, and prevent asset failures. The company's Electrical Submersible Pumps (ESP) played a critical role in their operations, but the manual methods for ESP monitoring and optimization were time-consuming, expensive, and prone to human error. Vital Energy wanted to create an AI-based solution for ESP optimization that would automatically recommend ESP operating parameters, provide visualization of all necessary data, and allow for feedback, input limitations, and operating constraints.

Pantheon, an independent software vendor (ISV) based in the Netherlands, was experiencing rapid growth and an increasing demand for its information and communication technology (ICT) services. The company provides custom ICT solutions, including enterprise resource planning (ERP), human resource management (HRM), and customer relationship management (CRM) software for wholesale and manufacturing companies. As more organizations, particularly small and medium enterprises, were moving to a cloud or hybrid cloud infrastructure, Pantheon saw a significant rise in demand for its cloud and hosting services. This required investments in a robust cloud foundation, including the purchase of new, scalable servers and accompanying software.

CosaTron, a company that provides high-value, remote air quality monitoring services for building owners and facilities managers, faced a significant challenge due to the COVID-19 pandemic. The urgency to monitor indoor air quality increased exponentially among their customers. This was primarily due to the heightened awareness and concern about the spread of the virus in enclosed spaces. Additionally, customers expressed a need to review the indoor air quality themselves. This requirement posed a challenge for CosaTron as it necessitated a solution that could provide real-time, remote monitoring of indoor air quality sensors, which was not part of their existing service offerings.

Openreach is a wholesale telecoms business providing engineering services to more than 650 communications providers, which sell the phone, broadband, and Ethernet services to UK homes and businesses. Openreach wanted to improve the customer experience by ensuring that jobs (e.g., telephony installations and repairs) were completed successfully the first time, every time, and on time. This was easier said than done because Openreach’s engineers needed to diagnose and fix a wide range of connectivity issues.To provide the best possible service, Openreach had to move beyond its traditional engineering mindset and put customers at the heart of its business.

JDE needed a partner with the expertise to provide a comprehensive overview of all cybersecurity risks and vulnerabilities across its factories. This included all operational technology computing systems used to manage the entire industrial operation.

The global bank, based out of North America, was facing a significant challenge in managing its report repository connected to dozens of applications and database systems used across the enterprise. The bank, serving close to 20 million customers worldwide, had to manually download hundreds of thousands of reports from these applications to a centralized location for use on a weekly basis. The file formats were typically unstructured data, usually in text or PDF, with no consistency in report formats across the different applications, or even for reports created using the same application. End users would then manually copy data from the text / PDF formats to Excel-based reports used for reconciliation, attestation, financial reporting, journal entries and other uses. This process was time-consuming, prone to human error, and inefficient.

Manual errors in warehouse managementProblems such as inventory theft, delayed shipment, and the need for double verification of inventory

Conserv and TEKTELIC Collaborate to Provide Indoor Monitoring Solutions to Protect and Maintain Valuable Artifacts and Collections Around the Globe.

To reduce time to market by speeding up cycle times, and reduce manufacturing and inventory costs, of complex building system automation equipment.

Simplifying maintenanceHana Financial Group had recently consolidated the infrastructure and resources of 11 of its affiliates at a local IBM data centre. However, the business was left with more than 100 service and maintenance contracts that needed to be reviewed and renewed periodically. These contracts also involved 100 separate bills that Hana Financial Group had to manage. Managing such a large volume of bills was cumbersome and sometimes resulted in late payments. The group wanted to improve efficiency and eliminate the overhead involved with managing these contracts by consolidating its heterogeneous IT systems and data storage systems under more consistent processes.

To optimize its Sigma Smart AirService, Kaeser worked with SAPDigital Business Services to deploySAP Leonardo IoT capabilities as its innovation foundation together with SAP Asset Intelligence Network and SAP Predictive Maintenance and Service. Kaeser’s new solution connects its compressors smartly in the cloud, allowing it to offer a next-generation service at a lower price.Challenges:- Service team unable to access calibration data and other equipment-specific information, which was stored in on-premise systems- No solution to meet the needs of dealers and companies’ service providers- Need for track-and-trace capabilities with selected suppliers to scale-up potential

The calendar machine run by a motor has a shaft mounted gearbox connected to the roller. This gearbox allows maximum paper load and feeds the paper with reduced speed to the roller. In spite of scheduled preventive maintenance, it was observed that gearbox used to fail frequently. The rise in vibrations leading to the eventual failure of gearbox adversely affected the quality of the paper. Monitoring the gearbox was thus vital and critical.

Extra loop of manual double-checks is needed in automotive quality inspections.

Quality management in this facility was only done at the end of the production process. This makes it hard to link scrap output to its root causes and understand when and why faulty bricks are being produced. This makes the process not only unpredictable but also inefficient.

The company, a leading manufacturer of heating, ventilation, and air conditioning (HVAC) systems, was seeking to leverage the Internet of Things (IoT) to enhance the capabilities of its large-scale HVAC systems. These systems are typically installed in large developments such as college campuses, commercial office buildings, and hospitals. The company was particularly interested in enabling predictive maintenance, as servicing major HVAC systems is expensive and a prolonged outage can cause significant disruption. However, implementing a predictive maintenance system involves building out a complex IoT architecture. A large number of sensors and devices have to be connected to a centralized management system. The company may have hundreds if not thousands of HVAC assets in the field, all of different types and models. These devices may be spread over different regions, which means managing and negotiating with multiple network operators. To enable remote monitoring, there also has to be a stable and secure connectivity.

The automotive industry has been facing challenges with the traditional drape forming process, a method used to adhere materials to car interiors. The conventional process uses a metal tool with heating and cooling channels to glue materials like leather onto car interiors. However, the tool, made by milling solid metal blocks, only allows for straight-line drilling of channels, limiting design possibilities. This limitation often leads to long cycle times and inconsistent heating and spreading of the glue, resulting in time and material wastage when the outcome doesn't meet the strict quality standards of the industry. The challenge was to eliminate these issues caused by using conventionally manufactured tools.

Tronergy, a company that provides creative IT solutions to small and medium-sized businesses, faced a challenge with its clients who were accustomed to using traditional web hosting services. As these clients' projects evolved, they found it difficult to dynamically and automatically increase bandwidth or improve performance using traditional web hosting solutions. Additionally, these clients often required the integration of several other business solutions to quickly customize their projects, such as adding text messaging (SMS), optical character recognition (OCR), email push, and chatbot features. Building a new solution from scratch was not a viable option due to the high time and cost implications.

Laminated fibre-reinforced polymer (FRP) matrix composites are increasingly used in industries such as aerospace due to their excellent mechanical properties and highly-tailorable design. However, this tailorability can negatively impact costs, productivity, and sustainability during manufacture, especially in machining where FRP part-specific defects occur. Process uncertainties resulting in large, unpredictable defect generation are a common cause for prescribing overly-conservative cutting tool use limits, based on part quality criteria. Due to the wide array of tool designs and workpiece material configurations available, an application-specific approach is required to identify the most effective cutting strategies. Optimal cutting parameters can be found using an exhaustive, wide-boundary, DoE-based approach, with slow and costly testing required to identify absolute tool life limits. The challenge was to establish a novel machine learning-based method to predict tool life from start-of-life performance data, reducing experimental time and cost. The project was particularly challenging, because the original dataset was sparse, with 82% of the target data missing.

Ryerson aimed to distinguish itself from competitors by improving customer service functionality, but supporting IT infrastructure needed an upgrade to deliver on its goals

ZettaNet, a privately-held company based in Perth, Australia, was facing a significant challenge due to the exponential demand for enterprise network, data center, and cloud services in the region. The company's business growth necessitated an upgrade of their core network to meet the increasing bandwidth requirements of their customers. The customers, which primarily include managed service providers, were demanding 1 Gbps connectivity between locations. These service providers then deliver network, data center, cloud, and voice services to a diverse range of customers including local businesses, schools, hospitals, residential communities, and government offices in Western and Southern Australia. The challenge for ZettaNet was to meet this high-capacity network services demand while maintaining profitability.

Optima Energy Systems, a leading energy management software provider, was facing challenges with its existing reporting system. The company had built an extensive collection of bespoke reports for its customers, which included large, multi-site organizations like supermarkets, water companies, telecom companies, and universities. However, every new customer required a different report, leading to a messy pile-up of options and settings that became increasingly cumbersome and difficult to support. The original reporting technology was unfamiliar to many, causing Optima Energy Systems to spend a disproportionate amount of time manually building reports rather than focusing on future product enhancements. The company sought to replace its existing reporting capability to improve development efficiency and transform its manual and resource-intensive reporting environment into a customer self-service reporting infrastructure.

CleanTelligent Software, a company that aids in-house and contracted janitorial teams in streamlining communication and improving quality control, faced a significant challenge. Their clients were demanding a more dynamic way to present reporting data. The company's software was primarily used to analyze and summarize a custodial team's performance, replacing a highly manual, paper-driven process. However, the initial differences between service providers in the janitorial industry are often unclear, and the cost of switching is comparatively low. This situation led to high client turnover, with a janitorial company's customer lifetime averaging four years or less. CleanTelligent needed to improve the customer experience with dynamic dashboards and reporting, retain customers through predictive analysis, capitalize on advanced analytics capabilities to build market differentiation, and improve client retention rates.