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.

SAP was grappling with the challenge of managing an increasing number of cloud deals. The rise in configurable cloud component deals necessitated a reduction in manual activity and a scaling up and automation of processes for order management, master data maintenance, and financial reporting. The high volume of cloud deals required a swift and efficient response, which was difficult to achieve with the existing manual processes. The challenge was to automate these processes to meet the growing demand and improve efficiency.

OptConnect, a provider of managed end-to-end wireless solutions for devices such as ATMs, retail kiosks, and digital signage, identified an opportunity to expand its market by developing an affordable, easy-to-install cellular end device. The company envisioned Neo, a small, plug-and-play device that customers could use to quickly link their systems to the OptConnect service. The challenge was to create a small, sturdy, reliable device that could integrate OptConnect's sophisticated management software, thereby enabling the company to reach the largest possible market. The device needed to leverage modern, high-speed 4G LTE cellular data connectivity, while being simple and highly reliable.

Tata BlueScope Steel, a leading steel company in the Asia Pacific region, was facing several challenges in its cybersecurity landscape. The company was struggling with a lag in real-time monitoring and frequent endpoint security issues related to security management. Their defensive approach to cybersecurity was proving to be inadequate in an evolving threat landscape. The lack of a Security Operations Center (SOC) to monitor the organization’s security environment 24x7 was a significant concern. The company was also aware of the increasing sophistication of threats and the need to neutralize them before they targeted their IT ecosystem. Additionally, the organization had experienced multiple phishing incidents, and addressing them was a key challenge. The pandemic-induced remote working scenario further exacerbated the situation, making the workforce more susceptible to attacks. Tata BlueScope wanted to extend security to employees working remotely and address the risk from zero-day attacks.

The challenges are as follows:Extreme traffic congestionDegradation of ambient air qualityLack of forecasts for traffic operationsLack of transit fleet operation information from varied transportation systems

A multinational insurer had heavily invested in Azure five years ago and was now facing a challenge with cloud expansion. The company had around 20 application sites and over 450 user sites to interconnect, and it wanted to maintain seamless operations. More importantly, it wanted to ensure consistent policy enforcement, security, and risk management across its entire hybrid estate. The security and risk team had mandated the use of private IP for internal network resources. However, the cloud team, without fully understanding the networking implications, deployed Private Endpoints in Azure to secure the IP. This made it impossible to resolve DNS and ensure connectivity between data center resources and Azure DNS zones. The cloud team realized that they could not meet both their security and scalability requirements using their Azure toolset alone.

Agilent Technologies, a leading American public research, development, and manufacturing company, was seeking ways to reduce its energy and water consumption to lower its environmental footprint and operating and maintenance costs. The company identified lighting as a significant area where immediate savings could be achieved. The existing lighting system was inefficient, often leaving all 50,000 square feet of lights on unnecessarily, leading to significant energy wastage. The company was also looking to reduce its operating expenses and meet sustainability targets. The challenge was to find a solution that would provide complete control over the lighting systems at their facility, reduce energy consumption, and offer flexibility in programming.

A leading medical technology company with nearly $20 billion in annual revenue and over 70,000 employees worldwide faced a complex challenge in managing network connections between its medical devices and service staff. The company had recently connected all its devices to the internet for remote diagnostics and updates, but this introduced several issues. Firstly, under the Health Insurance Portability and Accountability Act (HIPAA), all connections between medical devices and the company’s servers had to be encrypted, requiring the creation and management of separate VPN tunnels for over 15,000 field-deployed devices. Secondly, the devices, deployed in various medical centers and clinics, were assigned IP addresses by the network teams of each facility, often without coordination, leading to potential IP address conflicts. Lastly, the company’s network infrastructure, shaped by multiple mergers, acquisitions, strategic initiatives, and partnerships, was complex and difficult to manage, especially with the recent adoption of AWS cloud for much of its internal compute.

captures vibration & other environmental data in real time through sensors installed on various components of industrial equipment like Turbines, pumpsgenerates insights to help predict downtimes and thereby enable customer to maintain systems health & equipment efficiency.processes the high volume, high frequency data to monitor, analyze & alert about machine condition. 

Whether protecting a VIP, evacuating a hot zone, or dealing with highly sensitive data or physical assets, a global intelligence and threat management firm TAM-C Solutions applies a strategic, data-driven approach that produces results, no matter how difficult the circumstances, identifying threats to client personnel, operations, assets, and the client’s brand.  For instance, at the height of the COVID-19 breakout, TAM-C was responsible for managing the logistics for the high-profile evacuation of a group of students stranded in Lima, Peru. The private agency simultaneously coordinated flights out of the country and travel from remote regions to the U.S. Embassy without incident.  Battle-Tested, Client-Focused“TAM-C’s analysts work in extremely close proximity to our clients, which include Fortune 100 companies, academic institutions, non-governmental organizations, and humanitarian agencies all over the world,” says Richman. “It’s not uncommon to have 50 or more staff working at a client’s facility off-site, supporting them on a 24x7 basis. It’s part of our relationship with them, a partnership we forge with each client.” TAM-C’s specialized services rely on its proprietary Fusion system, a patented artificial intelligence platform that perpetually collects and collates data from a wide range of sources. These include publicly available information via social media and the dark web, data on groups and persons of interest, and threats from extremist factions. Fusion automatically analyzes and ranks all collected data by relevance. The findings are assessed by highly skilled security analysts, who then coordinate with teams assigned to client organizations.  

Comcast Business, a division of Comcast, was looking for ways to modernize the Enterprise Resource Planning (ERP) system of one of their enterprise customers, a local building supply company. The customer was seeking a new IT solution to upgrade their ERP system. Keeping all functions on-premises would require a complete rebuild of their existing data center, leading to a significant capital cost burden and ongoing expenses to scale over time. This option was not ideal, so alternatives were explored. Public cloud solutions available through AWS were the best fit, but accessing these services via their existing public internet was slow and did not meet the network latency thresholds needed for their new desired architecture. Ongoing operating costs were also a concern, so a scalable, cost-effective solution was needed.

Before implementing our safety software solution, Michael Armitage, EHS Manager noted how Siemens had a lot of business units using different systems for the recording of EHS events. There was a clear need for a more efficient system for managing EHS data which would fit both client and divisional reporting requirements. The biggest issue with each business unit using a different H&S system was that a lot of them were using old databases and in some cases, Excel spreadsheets. Risk assessments, inspections and audits, method statements and training all sat separately with little or no interaction.

Wavenet Technology, a digital marketing company, assists global brands in optimizing their online marketing campaigns using artificial intelligence and big data analytics. Customers access a web dashboard to monitor their campaigns’ performance in real time. However, as the number of simultaneous dashboard queries exceeded one million, the time to extract, transform, and load (ETL) data for the reports became increasingly lengthy. The processing exceeded the capacity of Wavenet Technology’s systems, which were running on AWS Redshift, causing customers to wait several minutes for the systems to respond. This situation began to hinder Wavenet Technology’s business development plans, prompting the company to seek a high-performance, secure, and affordable database that could support its growth targets.

Auto IT, a leading B2B dealer management software system (DMS) company in the Australasian region, faced a significant challenge with its clients' reporting processes. Prior to adopting Yellowfin, Auto IT’s clients relied heavily on Microsoft Excel spreadsheets for reporting, a largely manual and inefficient workflow that was not mobile-friendly and lacked modern analytics features such as visualization. As an Independent Software Vendor (ISV) partner, Auto IT needed an analytics solution that could support its customers' growing analytical requirements. The inefficiencies and limitations of the existing reporting system were the primary drivers behind Auto IT's decision to seek a Business Intelligence (BI) and analytics solution.

Parkland Health, a renowned healthcare institution, was facing several challenges in managing its clinical asset ecosystem. The existing data validity was not meeting the requirements of the Clinical Engineering (CE) and Information Security (IS) teams. The existing workflows were not aligned with the strategic vision of the leadership. The institution was unable to dynamically update their computerized maintenance management system (CMMS), which was crucial for efficient asset management. There were significant change-management hurdles between isolated teams, which were hindering the smooth execution of projects. Moreover, Parkland had allocated an insufficient budget to maintain project momentum and meet all expected outcomes.

ARD Logistics, a global provider of Supply Chain Management services, faced a significant challenge in delivering parts to a major luxury auto manufacturer. The delivery had to be executed Just-In-Time (JIT) and Just-in-Sequence (JIS), with Very Narrow Aisle Storage (VNA) and utilizing an Automated Storage Retrieval System (ASRS). The company needed a fully integrated warehouse management system that could meet these specific requirements and optimize the loading of Specialized Delivery/Transportation by their fleet of box trucks. The challenge was not only to meet the stringent delivery requirements but also to ensure the system was fully integrated and capable of managing the complex logistics operations.

Uline, a leading distributor of shipping and packaging solutions in North America, was facing a challenge with its lighting system. The company, known for its customer service, order accuracy, quick delivery, and low prices, needed its facilities to operate at peak efficiency. This included the 3,014 lights in its 800,000 square foot facility in Lacey, Washington. The company's Director of Engineering, Mike McConnell, was tasked with finding efficiency in every corner of the facility, including optimizing light to improve both operational and financial performance. The company had identified a luminaire that fit their needs, but struggled to find a reliable lighting controls provider that could deliver a solution at this scale to meet stringent energy codes and zoning requirements. The lights in the entire facility had to operate as a single system with one interface, adjust to natural lights from the skylights for daylight harvesting, and work with Uline’s existing IT systems. Other providers offered a mix of wired and wireless systems that were complex, hard to install and maintain, and couldn't scale to meet the size of the facility.

In commercial buildings, temperature, humidity, and air quality are all important for people's health and productivity. High levels of CO2 inside commercial buildings can cause many health concerns, commonly known as SBS (Sick Building Syndrome). Increasingly sophisticated smart buildings are being developed by nations around the world to improve efficiency, reduce costs, and generally make the environment healthy for residents and business owners. Additionally, under the looming climate crisis, energy prices began soaring last year. The need for building energy usage optimization has never been this urgent.The AI-driven system requires accurate and real-time environmental data for analysts to provide alerts and recommendations to the building operators when sensors show that pre-determined thresholds have been exceeded, or to optimize the building's operation to save money. The existing sensor system functioned poorly with critical problems:Poor SignalThe original solution was based on a techonology with limited signal coverage, up to 60% of sensors onsite were down at any moment.Excess MaintenanceThe original solution was based on a techonology with limited signal coverage, up to 60% of sensors onsite were down at any moment.Extra ExpenseEach Temperature and CO2 sensor required a sim card that generated an extra $500 monthly for each floor.

ACCIONA spent significant time and resources manually testing water samples in a laboratory to determine chemical concentrations. Due to the time it took to obtain these results, they were often outdated and unreliable. This resulted inadditional costs related to chemical supply and regulatory penalties.By implementing real-time optimized Machine Learning control algorithms at each of its desalination plants, ACCIONA was able to minimize the use of reactive chemicals, eliminate associated regulatory penalties, and provide an efficient edge infrastructure to implement new applications for predictive maintenance, energy efficiency, sensing, optimization or reinforcement learning.

Heerema Fabrication Group (HFG), a leading company in the offshore oil & gas and energy, engineering and construction industry, was facing a significant challenge. For over a decade, HFG had been using custom-built software for its primary business process. However, with the company's revised strategy of becoming a global EPC(I) contractor, the legacy software rapidly became obsolete. A new ERP software was necessary to support HFG's emphasis on becoming a global player in engineering, procurement, construction and installation (EPC(I)) and turn-key contracting. The company needed a solution that would support its core processes, facilitate collaboration with subcontractors, and provide project management support for EPC(I) projects. The challenge was to find a solution that would meet these requirements while also being financially viable.

A large power utility in Hawaii was looking for more frequent condition monitoring on their Balance of Plant (BOP) generation assets. They had experienced significant equipment failures that occurred between their scheduled quarterly walkaround condition monitoring routes.

From the sorting and analysis of past cases of digital construction in the energy field, four problems are often encountered in the process of digital upgrading of the energy industry, including the difficulty of using data in the early stage of construction, the diverse and volatile needs in the middle stage of construction, and the later stage of construction., the lack of continuous operation capability and the mismatch of safety requirements, etc.Data is difficult to use: while the amount of data is exploding, the data chimney still exists. According to the statistical analysis of relevant institutions, about 80% of the data has not been effectively used due to data silos and lack of analysis capabilities.Diverse and volatile demands: supply and demand sides, production links, and business departments have different demands for data usage. Business scenarios are complex and have low fault tolerance, making it difficult to get through the CPS (information physical system).Lack of continuous operation capability: business applications and data construction are separated, and data services cannot cope with rapid changes in business, resulting in a lack of depth and breadth of operational services and a significant drop in customer satisfaction.Mismatched security performance: comprehensive energy services require extensive access to customer data, and it is difficult to avoid data interaction security issues between internal and external networks.

The customer, a US-based global leader in delivering efficient solar shade systems, sought to modernize their existing product line by incorporating Internet of Things (IoT) connectivity. Their product line consisted of shade controller devices and systems, and they aimed to enhance occupant productivity and comfort, enable third-party integrations, and improve device performance and field servicing. The challenge was to devise a reliable and comprehensive IoT-led solution that could seamlessly integrate with their existing devices and applications. The customer partnered with Softdel to achieve this transformation.

The case study compilation presents a variety of challenges faced by different organizations across various sectors. Medical Industrie GmbH & Co. KG needed to optimize and streamline their B2B sales. Bank Sinarmas needed to comply with Indonesian Open-API Standards and exploit the ecosystem economy. MUDUM required a platform to harness the power of the API-driven ecosystem economy. OCP Group needed to standardize their APIs. Al Barid Bank was in the process of digital transformation. Marsa Maroc needed to digitalize its business workflows. PharmLog required an integration platform for seamless pharma logistics. Lufthansa Technik AG needed a B2B integration environment for standardized customer engagement. Socomec needed a hybrid integration tool to boost security and improve efficiency. Hellmann needed to integrate more than 750 application interfaces and over 500 customers.

Wiscon Products, a precision parts manufacturer, faced a significant challenge in data accuracy. The company's manual data collection methods were outdated and inefficient, often resulting in data that was several days to a week old by the time it was reviewed. This lack of real-time data made it difficult for the company to make informed decisions and implement improvements. Wiscon also struggled with gaining insight into production downtime, cycle time, and equipment utilization. The company had questions about how often spindles were turning and how many parts were being produced. Despite investing over $16 million on equipment, Wiscon was always running at capacity, and there were gaps and delays in the data, leading to a lack of visibility and an inability to respond to issues quickly.

To have the most robust, secure, and effective IT architecture possible.To achieve the highly available IT infrastructure that Stevanato required, a rigorous networking architecture was combined with an equally strict server architecture in two connected data centers between Padua and Bologna. 

Modernize Japan’s financial services sectorTo improve operational efficiency, Japanese financial institutions urgently needed to modernize their legacy systems. The industry faced several challenges, including flexibility, development speed, and complex regulations. To address these issues, NTT DATA wanted to build an innovative financial services delivery platform using open source technologies. The company chose Red Hat hybrid cloud and automation technologies to develop, deploy, and automate new applications for its banking customers.

DataVita, a leading data center, faced a significant challenge in maintaining their service level agreements (SLAs) with clients. The company guarantees 100% uptime, and any drop in availability, even for a second, would result in a 25% return of a customer’s quarterly fees. To uphold this commitment, DataVita needed a cost-effective solution for rack-level temperature and humidity monitoring in their 4,000 sq. m. data center. The company sought an experienced partner to design and deploy a monitoring solution that would protect both their customers and their revenue.