ABC faced two major issues when utilizing the data collected. One is the size, complexity, and disparity of the data collected would take lot of man-hours to process and evaluate. Two is real-time data cannot be put into use due to the nature of data science analysis.

For the development of its new wide-body aircraft, Airbus needed to ensure quality and consistency across all internal and external stakeholders. Airbus had many challenges including a very aggressive development schedule and the need to ramp up production quickly to satisfy their delivery commitments. The lack of communication extended design time and introduced errors that drove up costs.

The world's 1st-ever Industrial Internet platform, Predix, becomes a pathway for revenue generation and notable new cost savings for Pitney Bowes' production mail business. An ordinary mail business, this is not. Of the 150 million pieces of mail produced each day in the US, the majority go through Pitney Bowes machines.

Midea's outdated IT infrastructure in some sites could no longer keep pace with company's growth, putting operational reliability at risk. The legacy data backup system could not backup at some production sites. Some sites were still using the x86 server’s local hard disks as the backup media, resulting in limited backup size. The existing backup system was inefficient.

Nobilia manufactures customized fitted kitchens with a lot size of 1. They require maximum transparency of tracking design data and individual processing steps so that they can locate a particular piece of kitchen furniture in the sequence of processes.

While Faurecia has a long track record of providing its customers with exemplary products, the increasing need to provide customers traceability for the parts it was producing motivated the company to further support these efforts. The large automotive OEMs expected Faurecia to be able to both track the process of operations and production and to make that information available on demand. For example, customers wanted to know which airbags were added to which cars, as well as detailed data characteristics about how each airbag was installed, including torque and angle of installation.

Schneider Automation wanted a solution to its PLCs on the factory floor so that they can meet cost target for manufacturing systems. The challenges were that the solution needed to connect smaller PLCs and embedded devices that have limited storages or processing capacities.

As a part of their Industry 4.0 initiative, the customer primarily wished to leverage IoT for maximizing operational efficiencies, productivity, reducing the energy footprints and maximizing capacity utilization. But there were several challenges at the outset:Firstly, the customer had multiple assembly lines with a diverse set of machines, systems and sensors, all communicating on different protocols. As such, primarily they needed a partner who could connect diverse set of assets on to a single platform and make use of underutilized ‘dark’ data.Secondly, the amount of data, data types and their applications was so vast, that the platform handling it, needed to be scalable and flexible.Lastly, Varroc faced the typical challenge of innovating in ‘Brownfield’ markets – wherein the real bottleneck is in integrating IoT in tandem with both the new and legacy equipment without any further CAPEX for asset substitution.

VISIBILITY - Currently unable to see amount of power consumed per machine or plant; need to account for energy used per batch. WASTE - 10% of product fails quality standards, unable to identify point of failure (initial spinning, weaving, final processing, etc). INACCURACY - Acquiring OEE measurements and compiling them is a manual process, which lacks visibility into all parts of the production process and is error-prone. LACK OF INTEROPERABILITY - Outdated machinery still has long, effective lifespans but needs to connect to newer, digital assets

A large amount of engineering work involving frequent specification changes not only resulted in a nightmare for staff but also caused a considerable amount of material wastage due to miscommunication and last minute change notices. Need a system that is not too complicated to manage, and is easy to learn and use for typical employees because there a shortage of specialist IT staff and the company employs many short-term contract employees. Need an application that is not too expensive to implement, easy to use and powerful enough to handle a large volume of work.

The leading CPG company operates several warehouses, mostly closer to the last distribution point (Large retailers). Products in various categories are packaged in specific delivery or display cartons at these facilities. As most CPG businesses consist of high volume with low margins, optimizing every operation and effective utilization of resources add up to profit margins. The key problem at these warehouses is the lack of visibility into reasons for machine breakdowns or idle time, thereby delay in delivery. The sunrise meetings lead to post-mortem of delivery issues like delay or quality. The customer wanted to implement real-time line monitoring and alert system to gain control over downtime issues and implement improvement measures.

Inaccurate order picking and resulting loss of customer satisfaction.

The customer’s manufacturing process takes raw aluminum billets and uses a cold rolling process to produce rolled aluminum goods. A throughput bottleneck was identified at the cooling station as the existing temperature measurement process required the crane operator to climb down from the crane regularly and perform direct measurements on the rolls.

The client wanted the system to go-live in a short duration of time and it is very critical for them to do this before their production. They wanted a strong SAP (System Application and Products) implementation partner with expertise and experience in the manufacturing domain, especially with expertise in the automotive and Supply Chain space.The client wanted their SAP system to be aligned with their business processes and wanted to derive maximum benefits out of their SAP investments. The client was very particular about having a robust and operational SAP system much ahead of their production timelines.

Tetro factory had the following challenges: - Controlling the production flow, tracing mistakes and optimizing performance. - Running a fully integrated knowledge-based business with systems that work seamlessly together. - Centralizing manufacturing production data into one system that can be viewed and analyzed from a single-point-of-entry. - Pinpointing in real-time which stations are compromising production and what can be done to restore and improve efficiency. -Implementing preventative maintenance and ensuring minimum downtime. - Monitoring energy consumption and optimizing material consumption per product.

This document summarizes the manufacturing execution system (MES), or manufacturing operations management (MOM) solution implemented by a leading Automotive manufacturer to manage the complex assembly of the engine for their new Supercar. The MES/MOM was integral to ensure each and every single of the nearly two-thousand (2,000) process steps involved to build the engine were completed to the set specifications or tolerances without fail. MES/MOM ensured zero-defects during the assembly of the engines since it monitored and controlled all operations; all tools and devices, and the line workers themselves since the MES/MOM directed them from job start to end. The MES/MOM verified worker credentials, provided work instructions, and confirmed that the materials and tools were properly selected for the exact task at hand. Destined for the Automotive manufacturer’s highest-performance GT sports car (see Figure 1), the twin-turbo charged V6 “EcoBoost” engine is vital to the success of the final product. Given the intricacy of the engine and the number of steps needed to assemble it, and its high tolerances, the MES/MOM proved indispensable.

When UTC Aerospace required a solution to manage assembly line workers with no previous manufacturing experience, it decided to try something new that set a precedent for its future manufacturing operations management (MOM) strategy.

GE Aviation loses millions of dollars each year to errors made at key points during the assembly and overhaul of its engines. The costs show up in lost productivity, delays in testing, delays in customer deliveries, and the man-hours required to troubleshoot and correct faults. If errors arenʼt detected until after the engines are sent to customers, the repair costs exponentially increase.B-nuts are one such key manufacturing point. They play a critical role in aircraft engine fluid lines and hoses, providing a sturdy, reliable seal―but only if tightened and torqued properly. If not torqued properly, there will be a need for a maintenance do-over, cancelled flight, or even an in-flight shut down.

High quality standards and full material traceability are essentialrequirements for identification solutions in the automotiveindustry. Parts identification and container management areconsidered to be important factors for a problem-free productionprocess. The labels must also retain their adhesive properties on many different types of surfaces - from porous structures to oilymaterials. The labels should also be able to withstand rugged, high-temperature environments without tearing or peeling off.

The cosmetics market requires manufacturers to make quick changes in the matters of both production and distribution. In this market segment, one of the principal marketing tools is grouping products in packages (for example, shampoo + conditioner, cream + makeup remover). So far such process has been carried out in the Polish division of L’Oréal through outsourcing, which has limited the possibilities of a dynamic reaction to market impulses.