In the automotive industry, niche products are becoming more and more important. The automobile industry has changed considerably over the past few years. No doubt: to remain competitive, instant reaction to specific customer requests is of utmost importance. In a parallel to the growing individualization of our society, the range of models available from Audi has increased as well.

In today’s manufacturing facilities, there is a large mix of heterogeneous machines and control types, where signals must be collected, aggregated and evaluated. The solution to this common problem is a centralized system, which can seamlessly “plug and play” with any type of machine CNC controller or PLC. However, machine connection and integration capabilities are key differentiators when selecting the right MES technology provider. The experience level and readiness of the technology provider determines the time and costs required to successfully connect any machine. Standardized interfaces to all common machine controls, via direct plug-ins, must be created, otherwise the time required for connecting the machines, is unmanageable. In a pilot project initiated by an MES provider, a major German tool manufacturer determined that connections to some of their machines were very time-consuming, costly and in some cases not possible. Even after months of work, some challenging machine controls types remained unconnected. The MES provider lacked expertise and the necessary plug-ins.

Manufacturing processes in aerospace machine shops can be complicated and complex to plan. Finding out how much capacity is really needed for a part to be produced, and accurately planning the total throughput time for a range of components can be a headache for many manufacturers. Often, it can be difficult to do accurate part costing, as many cost centres are involved, and blended rates are used as there are is no exact data on machines and work stations in a process. Many aerospace companies have vast untapped potential for reducing costs by improving processes, reducing WIP and faster throughput times, but in most cases they have no tangible data to base cost saving improvements on. UK aerospace companies are notorious for their excellent technical knowledge and high quality products. But the manufacturing process itself is often far from efficient. The orders are there, the requirements are clear, but capacities are limited and many battle with considerable overload on the shop floor.

Full traceability of all processes and products is critical to success in any business. A modern traceability solution is necessary to ensure reliable error analysis, rapid shutdown of vulnerabilities, and higher quality. The solution must consider all supply and value chains and support the connection of machinery and equipment seamlessly. A medium-sized automotive supplier struggled to integrate a suitable traceability solution for their shop floor. After a year of changes, configurations, and patches, the MES still did not work properly, and employees complained about poor usability. The management then consulted FORCAM.

BorgWarner Cooling Systems, a subsidiary of U.S. Automotive Supplier BorgWarner, aimed to optimize production at their German plant. The plant, which houses a total of 40 machines, was in need of a system that could systematically collect and process machine and operating data, visualize current process states online, and precisely analyze weak areas. The goal was to increase overall production efficiency. The challenge was to develop and implement an individual, custom-fit production management system that could meet these needs.

C.S.YAP Group of Companies, a market leader of metal parts to different industries in Malaysia, faced significant challenges in their manufacturing process. The process was complex and could be impacted by many factors such as supplies, equipment, factory overhead, the need for special parts, and the people who work at all points in the process. The more variables there were, the greater the possibility of disruption to the smooth operations of the factory. Management styles and workforce could also have an impact on this process. For instance, human insight into a manufacturing process leading to more labor-efficient and cost-effective methods of production could affect the manufacturing process in a positive way. Not only did the operator need to understand the basic machining operations, correct tool usage, and correct speed of operation but also detect tool wear and replacement patterns. Skilled machinists usually made these decisions based on experience with no written instructions other than a blueprint of the designed part. Often this involved setting up the machine tool, running a few pieces through to test the arrangement, and then adjusting the setup until an acceptable part was produced. This could be a time-consuming and a tedious process.

In 2014, Nordson Corporation expanded its commitment to Continuous Improvement by introducing company-wide Key Performance Indicators (KPIs) and the Nordson Business System (NBS). The KPIs were designed to measure progress around critical performance drivers such as growth, profitability, productivity, asset utilization, and customer satisfaction. Nordson aggressively tracked and reported progress against these KPIs for every business unit. The NBS, rooted in Lean Six Sigma, was implemented to improve performance within each KPI. At Nordson Adhesive Dispensing Systems in Johns Creek, Georgia, the team determined that machine performance needed to be measured in real-time to quickly recognize and correct errors, reduce waste, and continuously optimize productivity. They reviewed available solutions and decided to implement the Shop Floor Management Technology provided by FORCAM.

GKN Aerospace, a leading aerospace supplier, faced the challenge of improving manufacturing productivity in a low-volume, high-mix environment. The company needed a solution to enhance machine utilization, reduce operation time, and improve overall efficiency. With strategic partnerships with major OEMs and tier-one suppliers, GKN Aerospace required a robust system to manage and analyze machine data in real-time, allowing for timely interventions and quality improvements. The company also aimed to integrate this system with their existing ERP SAP to further streamline operations and achieve continuous improvement.

Richards Industries, a parent company of six distinct industrial product lines, has been affected by the decline of crude oil, a key source of energy, which has created opportunities and threats for American manufacturing. The company's business has been slowed by the Oil and Gas reductions but has continuously invested in new product development, process improvements, lead time reduction, on-time shipments and quality. Richards Industries practices Lean Management philosophies for almost two decades. Investment in training and technology is key to retain talent and control cost. The company is dedicated to finding ways to improve manufacturing processes, existing products, creating new products, reaching new markets and responding faster to customers.

The medical device industry is a major part of the UK high value manufacturing sector, contributing billions every year to the economy. However, as the pace of technological change quickens, there is a need to control and manage production. This is particularly the case when new products are introduced and product integrity needs to be guaranteed. The faster the market moves, the more frequent changes in manufacturing processes come - and this is where errors increase. The human element bridging production systems always has the potential to introduce errors. The answer to this problem has come in form of Industry 4.0 solutions. Introducing Industry 4.0 and the application of manufacturing execution systems (MES) can mitigate many risks to product integrity.

The manufacturing industry is facing an abundance of complexity, which becomes more apparent with frequent product innovation and shorter product life cycles. Digitization and the ability to access information from anywhere and at any time are changing the rules in almost all sectors. Manufacturers must accelerate production cycles and distributors must shorten delivery times. In response to changing dynamics involving savvy consumer expectations, time to market, and intense global competition coupled with the Internet of Things and mobile technologies, the entire supply chain ecosystem is undergoing a vast transformation. With the many meanings of digital transformation at innovative companies, to remain competitive means to uncover potential for increased productivity and to unleash the hidden factory. Hard facts from machine data must be accessed, understood, and evaluated for effective intervention.

Audi, a pioneering car manufacturer, operates press plants in Ingolstadt and Neckarsulm, Germany. The automotive industry has seen significant changes over the years, with niche products becoming increasingly important. To remain competitive, Audi needed to respond instantly to specific customer requests. The range of models available from Audi has increased, which has implications for the manufacturing of car body panels. It requires the production of more sophisticated pressed parts, involving the use of a wide range of tooling. This necessitates creating capacities and improving the efficiency and performance of the press plants. More than 1,500 employees work with state-of-the-art press machinery at Audi's plants. The independent subdivision is responsible for the distinctive Audi design in aluminium and steel, making it one of the most efficient plants in the whole company.

The global aerospace industry is experiencing rapid growth, with a focus on production efficiency for both commercial and military projects. Aerospace suppliers like Dynomax and other manufacturers in the supply chain understand that staying ahead of the competition and meeting the growing need for finished products requires leaner production through technological investment. Dynomax, an aggressively growing aerospace supplier, rises to the challenge of smarter production and proactively drives greater capacity, speed to market, and overall competitiveness. The team determined that the performance of machines needed to be measured in real time to quickly recognize and correct errors, reduce waste and continuously optimize productivity. Key challenges included the collection of OEE / KPIs, full production transparency, identification of bottlenecks, Epicor ERP integration, machine utilization, and reduction in machine downtime.