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A major clean energy OEM was in need of a new Manufacturing Execution System (MES) that could handle two very different types of production and provide visibility across multiple manufacturing facilities. Their product is a complex industrial system with critical subassemblies produced using advanced chemistry and processing. With a new factory opening in a matter of weeks, their existing MES system was not adequate. The older system would not be able to scale to meet their new product manufacturing challenges. These challenges included the flexibility to handle product lines that are both high volume/low mix and low volume/high complexity, traceability of chemical modules produced in one facility and integrated into systems in another facility, variability and ease of use in the user interface to adapt to different manufacturing and operator setups, and providing complete visibility across several plants around the world.

A global medical device manufacturer had been producing complex Class II medical devices for years, using 42Q as their MES. Now they faced the challenge of manufacturing high volume Class III medical devices with complex, fully automated production lines. They feared that implementing advanced, high volume automation using 42Q MES would require significant factory downtime. The new production lines required a high level of sophisticated automation and a manufacturing execution system that supported and seamlessly integrated with such systems. The operational requirements included: Plans for volumes of 10 million devices per year, which required highspeed lines running 24 hours a day, 7 days a week. Manufacturing operations for a product that includes small components with dimensional tolerances of just a few microns (10-6 meter) in size. Handling these components manually and placing them in subassemblies with repeated precision required highly specialized robotic equipment. The stringent requirements of ISO 13485 and FDA regulations demands the repeatability automation provides with an MES that can handle high speed transactions. This device must be manufactured in a clean-room environment; automation reduces the number of people needed in the room. Thus, leading to less contamination. The system must automate backflush via connection to an Oracle-based inventory management system.

The industrial systems company was facing a challenge of implementing a Manufacturing Execution System (MES) across multiple plants. The company's product was complex, involving intricate subassemblies that required advanced processing at multiple plant locations. The company needed a flexible, easy-to-install MES that would enhance visibility across plants. The operations team began the evaluation process by reviewing on-premise solutions but excluded them based on high implementation costs, substantial recurring costs for maintenance, and high levels of expenditure and risk.

Cirtronics Corporation, a product manufacturer operating within multiple markets, was using MAX ERP and Aegis software as a Manufacturing Execution System (MES) to automate their manufacturing floor. However, they faced a challenge in streamlining the process of validating part numbers between Aegis and MAX—a process that could take most of a day when customers sent a new or revised bill of materials. The challenge was to create a seamless integration between MAX and Aegis so that information flowed quickly and smoothly between the two systems. If integration could be built, Cirtronics would be able to take full advantage of the best capabilities of each system.

Connor Solutions, one of the UK’s largest privately owned EMS providers, was facing increasing demands for compliance, control, and traceability in the Medical and Avionics sectors of electronics manufacturing. The company was relying on multiple systems to manage data integrity, which was becoming unsustainable due to the associated costs for increasingly complex operational management. The company decided to move towards a single holistic MES solution that would provide a single source of actionable live data, enabling them to achieve the next level of factory control, automation, visibility, and operational excellence.

Lear Shanghai, a subsidiary of the global Lear Corporation, was looking to eliminate rework and shorten new product introduction (NPI) time to improve their overall manufacturing process. As a supplier of automotive electrical distribution systems, their customers’ expectations for product quality and traceability were a key priority. The manufacturing process is quite complex, and the company’s main products include central control boxes, tire pressure monitoring systems, remote keyless entry units, and door sensor systems. Decision makers at the management level must balance their customers’ needs for product quality, on-time delivery, and traceability while minimizing their own production costs and increasing throughput. In 2008, as a new facility, it was crucial that decision makers choose an MES software that could be quickly and easily deployed throughout the facility to minimize the time it took to run as a fully functioning operation.

Norautron Suzhou, a subsidiary of Norautron Group, specializes in the manufacturing of high-mix, low-volume industrial electronics. In 2012, the company realized that their home-grown MES system could no longer support the growing demand from customers. The challenges they faced included increasing customer requirements and market regulations for mission-critical products. Products that need to work in tough environmental conditions or demand extremely high reliability like the ones Norautron makes for maritime, defense, and medical industries require traceability down to a single connection on a single electronic component. Also, process control and material management, including RMA is a must. However, the precise and high-level traceability and strict process control and management can only be achieved by a professional MES system, where Norautron’s home-grown system fell short. Ever-increasing time and labor cost while using and maintaining the home-grown system is another issue that troubled management. In the past, Norautron input tremendous labor-hours to create the trace record manually for each part and product to fulfill the traceability requirement and assure product quality. With increasing national wages, Norautron Suzhou found the labor cost, as a proportion of the whole operation cost rose so sharply year after year that company profitability was soon likely to be adversely affected.

Routine analytical assays in the cell and gene therapy sector often require repetitive and complex manual actions, which can be time-consuming and prone to human error. The Cell and Gene Therapy Catapult needed a solution to automate these processes, particularly for qPCR assays, to increase efficiency, data reproducibility, and walkaway time for scientists. Traditional automation solutions lacked flexibility and required advanced programming skills, creating a high barrier to entry for many biologists.

Syngenta was looking to improve their use of automation, and methods to make their protein production process more reproducible. Their three main pain points within their existing process were: Low uptake of automation for scientists across the Biologicals team. Automation is a powerful tool, but is difficult to use without considerable expertise. Think of trimming the edges of a poster but only being given a chainsaw; this is the feeling new automation users face, and one that Syngenta’s automation team wants to mitigate. Time-consuming processes refactoring complex liquid handler scripts. Even for expert users on Syngenta’s automation team, scaling automation for different numbers of samples is time intensive and requires careful validation in the lab to ensure the intended actions are scripted properly. This often results in reticence from scientists to invest their time in automation as they can do it quicker manually, which ultimately results in lower productivity over time. Insufficient traceability and reproducibility of experiments and data analyses. Machines improve reproducible execution of experiments, but they also increase throughput. This moved the bottleneck for Syngenta to the ability to track what has happened to each and every sample. While custom solutions were made in-house, their long term support persistence was low due to disparate documentation of the processes.

Pharmaceutical assay development groups work under constant time pressure and face increasing complexity without a commensurate increase in resources. As a result, these groups often adopt powerful statistical approaches such as DOE to shorten assay development cycles. DOE investigations enable the rapid optimization of many inputs and parameters simultaneously, offering the ability to quickly and easily execute and analyze higher-granularity, multifactorial characterizations of biological processes. Yet conventional DOE campaigns executed by hand still require weeks of iterative cycles, as the number of runs possible per cycle is limited by the need to minimize the complexity of manual calculation, liquid handling, and data collection tasks to avoid human error. The challenge for assay development is to increase the speed and accuracy of DoE campaigns by reducing time spent on planning, data aggregation, protocol execution, and liquid handling.

Scientists at Autolus routinely use cytotoxicity assays in the development of novel CAR T-cell therapies. Setting up these assays manually is labour-intensive and time-consuming. While automation can increase throughput, robustness, and walkaway time for scientists, it often requires advanced coding skills. In addition, automating the handling of live cells is not straightforward as they are sensitive and susceptible to lysis.

Oxford Biomedica faced challenges in handling the large volume of bioprocessing data generated from their lentiviral vector development process. The traditional methods of using spreadsheets and proprietary vendor software tools were cumbersome, resource-intensive, and prone to bias. The need for a scalable, flexible, and robust software tool to automate complex experiments and handle high-volume data streams was evident.

Oxford Biomedica faced the challenge of improving the efficiency and robustness of their in-house lentiviral vector production. The complexity of the biological system required a multifactorial experimental approach, which would have been very challenging to execute manually due to the number of experimental runs and the complexity of the design. Additionally, the high cost of therapy and the global demand for quality lentiviral vectors created a 'vector crunch' in the sector, necessitating the optimization of product quality, developability, and vector titres.

LabGenius faced the challenge of optimizing the single-stranded DNA (ssDNA) extension process, a critical step in their DNA library generation method. The process required different priming oligonucleotides for each ssDNA extension reaction, making it necessary to re-optimize the extension process for every new DNA library fragment. This repeated context-specific optimization was extremely challenging to execute manually due to the number of experimental runs and the complexity of the experimental designs. The need to recover maximum diversity during the single strand extension of DNA fragments encoding degeneracy was critical to the EVA platform. Manual execution within the expected time frames of DNA library generation was not feasible, necessitating an automated solution.

Identify efficient tools to predict productivity in yeast cell factories and optimize protein pathways. Enabling accurate genotype-to-phenotype predictions through machine learning. Exploiting the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.

MicroByre faced several challenges in their interdisciplinary research, including the inability to use off-the-shelf Laboratory Information Management Systems (LIMS) due to their unique requirements. They needed a personalized LIMS to increase efficiency and reduce costs of DNA designs, import and store data from legacy systems, and facilitate online collaboration and document sharing among teams. Additionally, they struggled with software that had complicated user interfaces and user experiences, which hindered their workflow and productivity.

Lanzatech was manually creating instructions for lab-automation equipment, which is a difficult, error-prone, and time-consuming process. They needed to develop an in-house BioDesign system for DNA assembly, workflow automation, and data management. Additionally, they faced challenges in implementing high-throughput experimentation and developing complex genetic designs. Integration with other platforms and systems that Lanzatech was using was also a significant challenge.

The CSIRO BioFoundry faced several challenges in integrating automation equipment with a Laboratory Information Management System (LIMS). They needed to explore a larger number of designs simultaneously, track items and changes in the state of samples, and reduce the time required to identify candidate strains successfully. Additionally, they required a system capable of generating and executing workflows while storing both phenotypic and genotypic data. These challenges necessitated a robust software infrastructure to support their high-throughput processes and machinery.

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.

Comprehensive Prosthetics & Orthotics (CPO) was facing challenges with their order processing and manufacturing workflow. The company's clinicians were sending plaster casts and clay impressions along with paper forms to their central fabrication facilities. This process often involved back-and-forth calls to rectify errors or clarify details. The order data was then manually transcribed and issued to the floor as a paper work order. During production, a job traveler moved through each work center, and technicians referenced the paper work orders for fabrication. Whenever a customer called with an order inquiry, it required a tedious process of going to the floor, locating the job traveler, and relaying the order status back to the customer. CPO needed a solution that would connect their clinics directly to the manufacturing floor, providing immediate visibility for customers and managers while streamlining the process for their technicians.

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.

The medical technology company faced several challenges in managing network connections between medical devices deployed in the field and the company’s service staff. The company had to ensure compliance with the Health Insurance Portability and Accountability Act (HIPAA), which required all connections between medical devices and the company’s servers to be encrypted. This involved creating and managing separate VPN tunnels for over 15,000 field-deployed devices. The company also faced network conflicts as the devices relied on the IT infrastructures of the medical centers and clinics where they were deployed. The devices were assigned IP addresses by the network teams of each facility, usually without any coordination. This introduced the potential that devices in different facilities would be assigned the same IP address, making remote monitoring and maintenance much harder to track. The company’s network infrastructure was complex due to multiple mergers, acquisitions, strategic initiatives, and partnerships. Maintaining visibility into the DNS of this complex enterprise was a significant challenge.

Codesigned, a technology services firm specializing in Microsoft SharePoint, needed a scalable, high-performance, enterprise-class infrastructure to accommodate growth and unpredictable client workloads. They also required a service provider with robust compliance measures and security levels to enable them to work with companies in highly regulated industries like healthcare. They sought a reliable and industry-proven cloud hosting platform. The company evaluated several large hosting companies, including Terremark, SunGard, and Dell, but found that most options did not provide the transparency and accessibility to their environment as well as a strong service mentality that could ensure a mutually beneficial partnership.

As Patronpath’s demand in the marketplace grew, the company began exploring options when it came to upgrading its computing infrastructure to keep up with demands. The organization realized the need for more IT personnel and infrastructure support, but could not justify the cost and resources to build and staff a datacenter from scratch. Patronpath began looking into cloud computing because it offered them the pay-as-you-grow pricing and scalability needed with unpredictable client workloads of online ordering for restaurants, which has the majority of server usage at lunch and dinner times. The biggest challenge and concern of moving to a cloud service was regulatory compliance and security. As the company handles online credit card transactions for its clients, Patronpath had specific requirements such as the Payment Card Industry Data Security Standard (PCIDSS). Patronpath needed the cloud providers being evaluated to demonstrate that they were in compliance with applicable regulations and could provide high levels of security before they would entrust their critical systems to the cloud.

WoundVision, a start-up in the wound care industry, developed advanced wound detection technology that utilizes personalized patient health data and infrared thermal imaging. However, as a start-up with limited resources and software that relies on a constantly updating and growing database, it was not feasible for WoundVision to host its own servers or manage and maintain them. The company's hosted application and database are accessed on hospital computers via standard internet connectivity, meaning a traditional on-premise solution would require each hospital to deploy or assign hardware plus constant updates to the database and application. Therefore, a cloud hosting provider with pay-as-you-grow pricing and scalability was necessary to host the company’s technology platform. A major concern for WoundVision was security. Providing a solution to the healthcare industry requires comprehensive security, strict records and data controls, forcing WoundVision to need to know exactly what is happening to the infrastructure and where the data is at all times.

eMeter, a global business, works with a number of installation partners to implement software solutions at utility companies around the world. They offer intensive “boot camp” training on how to properly install and manage its metering solutions. These boot camps are very system-intensive and require a lot of short-term resources to get an installation underway. After those first few weeks, their bandwidth requirements drop considerably. In the past, this meant buying enough hardware to absorb the impact of a heavy workload, with the full knowledge that the workload would soon change. A lot of their hardware was underused. The complicating factor for them is that it’s very difficult to buy a piece of equipment in India. Taxes and regulations are complicated. Some technologies aren’t available in every area of the country. As a result, it can take months to procure just one piece of hardware. To expand further into India—and to grow its footprint elsewhere—eMeter needed a more flexible solution for deploying compute resources on demand.

The financial services company, licensed in all 50 states for collections, relies heavily on their database-driven call center application. Any downtime results in financial loss and potential regulatory penalties due to the sensitive nature of the data they handle. With a small IT team, implementing an internal disaster recovery strategy was daunting, time-consuming, and expensive. The company needed a solution that would ensure real-time data replication, quick application recovery, and scalability as the company grows, all while keeping their IT team focused on strategic initiatives.