Manufacturing analytics in regulated industries with MachineMetrics on AWS

MachineMetrics on AWS supports automated production monitoring and analytics, while maintaining strong security and compliance. Users achieve strong security and compliance at scale, by using underlying MachineMetrics and AWS frameworks.

There’s a myth in the life sciences industry that cloud-based solutions threaten compliance due to a lack of security and stability. This level of caution can be understood – companies must comply with strict internal, federal, and international regulations. But this doesn’t mean that on-premises solutions are required. In fact, cloud software has become significantly more secure and stable over the past decade. There is a continued evolution of tooling and infrastructure, like the AWS Nitro System for Amazon Elastic Compute Cloud (Amazon EC2).

In this blog, we’ll discuss how manufacturers in regulated industries can obtain insights into the shop floor performance and have a strong regulatory and security compliance at the same time. We’ll show how manufacturers can focus on their processes and products while leveraging the compliance postures of MachineMetrics and AWS.

Cloud security and compliance

AWS is acquiring an ever-increasing set of regulatory certifications, and providing the tools and compliance attestations needed by customers in highly regulated industries. The Financial Services Industry (FSI), Healthcare, Life Sciences, Medical Devices, Energy, and Public Sector industries can all benefit. AWS has comprehensive tools and security capabilities that reduce the heavy lifting and operational burden associated with security. In the Life Sciences industry, a number of the most relevant medical device manufacturers have adopted cloud-based solutions without compromising compliance. This enables them to benefit from the flexibility, reliability, security, and affordability of the cloud.

At AWS, security is the top priority. AWS services are designed to meet the necessary security and regulatory requirements required by our customers. Cloud software is frequently updated, maintained, and secured by AWS, which helps AWS services to remain compliant over time. Organizations in the medical device manufacturing industry can use cloud-based solutions without comprising compliance. To take advantage of the compliance in the cloud, an organization’s security practices should include evaluations of your cloud provider’s security and compliance measures. Also implement a set of risk-sensitive controls aligned with the security architecture of the cloud platform. In addition, follow a strong process to align security controls with your solution requirements.

AWS supports over 140 security standards and compliance certifications, including GxP, the Health Insurance Portability and Accountability Act (HIPAA), HITRUST, the Personal Information Protection and Electronic Documents Act (PIPEDA), and the Federal Risk and Authorization Management Program (FedRAMP). This helps customers meet their compliance requirements worldwide. These security and compliance certifications can be used as inherited evidence for your own certifications.

AWS is responsible for managing and protecting the infrastructure that runs all of the services offered in the AWS Cloud. This infrastructure is composed of the hardware, software, networking, and facilities that run AWS services. AWS makes third-party attestation reports available through the AWS Artifact service within the AWS Management Console.

MachineMetrics production monitoring platform

MachineMetrics is a production monitoring platform that autonomously captures equipment data at scale and standardizes it into a common model. Context is then added to this data, such as operational data points (part rejection data and production run information). Users then have access to accurate, real-time production data. The data can inform out-of-the-box reports and dashboards, notifications, and automation workflows.

MachineMetrics on AWS enables device manufacturers to harness the power of real-time data to optimize their production processes, reduce downtime, and improve efficiency. By using the scalability, security, flexibility, and cost-effectiveness of AWS, MachineMetrics is able to provide manufacturers with a powerful and comprehensive platform. This platform provides manufacturing analytics, and enables device manufacturers to monitor and improve utilization, downtime, processes, and throughput.

Cloud shared responsibility

Figure 1 illustrates the Shared Responsibility Model between 1/ AWS, 2/ MachineMetrics, and 3/ MachineMetrics’ customers. AWS is responsible for the security of the cloud itself, such as the infrastructure services that support MachineMetrics production monitoring and analytics platform. MachineMetrics is responsible for their security in the cloud, and compliance of the solution they deploy and operate in the cloud.

Figure 1. The AWS shared responsibility model and MachineMetrics

With the undifferentiated effort handled by AWS, MachineMetrics can then focus on providing added value to the manufacturing customer. They can develop domain-specific microservices, network and firewall configurations, gateway management, data encryption, and data integrity authentication services.

Finally, MachineMetrics customers can focus on maintaining the security and integrity of the network on the plant floor. A bulk of their effort will go towards consuming and using the data output of MachineMetrics services, and their solution components, such as computerized maintenance management systems (CMMS).

MachineMetrics and AWS

For medical device manufacturers, secure data collection, processing, and storage is imperative to meeting standards and delivering quality products to customers in the most efficient manner possible. MachineMetrics supports this with a comprehensive machine connectivity platform that delivers not only rich quality data from the shop floor, but also tools to act on it.

Following are some of the AWS services that MachineMetrics uses. To ensure security of these services, MachineMetrics employs a variety of measures, including role-based authentication via AWS Identity and Access Management (IAM) to manage access with multiple AWS accounts. AWS CloudTrail is used to audit AWS API usage.

Amazon EC2. MachineMetrics uses Amazon EC2 to host its compute resources in their cloud infrastructure. EC2 provides scalable computing capacity in the cloud, so MachineMetrics can easily add or remove instances as needed to meet demand. For security, all instances are in private networks and not accessible from the public internet.
Amazon Relational Database Service (Amazon RDS). MachineMetrics uses Amazon RDS to host its databases. RDS is a managed database service that makes it easier to set up, operate, and scale a relational database in the cloud. The databases are encrypted and logs are exported to AWS CloudTrail.
Amazon Simple Storage Service (Amazon S3). MachineMetrics uses Amazon S3 to store and retrieve data. S3 provides scalable object storage for any type of data, so MachineMetrics can store and access large amounts of data quickly and cost-effectively. The buckets are encrypted and access is logged to track and maintain security.
Amazon Kinesis. MachineMetrics uses Amazon Kinesis to stream real-time data from manufacturing equipment to its platform. MachineMetrics uses Kinesis to process and analyze data as it is generated, which permits real-time monitoring and analysis of production processes.
Amazon CloudFront. MachineMetrics uses Amazon CloudFront to distribute its content globally. CloudFront is a content delivery network (CDN) that caches content at edge locations around the world. It improves performance and reduces latency for users accessing MachineMetrics’ platform from anywhere in the world.
AWS Lambda. MachineMetrics uses AWS Lambda to run serverless code in response to events. Lambda enables MachineMetrics to write code that automatically scales to meet demand, without the need to provision or manage servers.
Amazon Route 53. MachineMetrics uses Amazon Route 53 to manage its Domain Name System (DNS) routing. Route 53 is a scalable and highly available DNS service that makes it easy for MachineMetrics to route traffic to its platform.

By leveraging these AWS services, MachineMetrics is able to provide its customers with a reliable, scalable, and cost-effective platform for manufacturing analytics. With real-time monitoring and analysis of production processes, manufacturers can optimize their operations, reduce downtime, and improve efficiency, ultimately driving greater productivity and profitability.

Data collection, management, and quality

Medical device manufacturing dictates a set of compliance and security considerations requiring strict process control. Supporting the process control with actionable data has played a pivotal role in the delivery of quality products and overall business performance.

The data collection and management infrastructure of manufacturers has adapted over time from strictly manual processes to homegrown solutions and semiautomated collection and standardization systems. There have been advancements in closing the gap between enterprise and shop floor performance¹, as managers attempt to drive production data into business management systems like enterprise resource planning (ERP). This concept, also referred to as information technology-operational technology or IT-OT convergence, is unlocking visibility across the entire business to better understand the impact of shop floor performance on bottom-line financials.

Particular to the medical device manufacturing space, industrial data has in many ways remained siloed at the plant floor level due to concerns over cloud computing, mainly around security and compliance. With quality at the forefront of each organization’s production goals, collecting valuable production data means that frontline workers, managers, and enterprise executives have the information they need to make better decisions.

Connecting MachineMetrics to key shop floor systems like an ERP/manufacturing execution system (MES), or quality management systems and CMMS, extends the value of the data. It ensures an accurate representation of shop floor performance in the management system. As shown in Figure 2, this is especially useful for an enterprise with multiple plants.

Figure 2. Data integration with MachineMetrics

MachineMetrics provides many quality tracking and reporting features. An operator can reject a part via the Operator View through tablets mounted at the machine, and quality managers are then able to view the quality data via Pareto charts. This quickly identifies where scrap is occurring, how much scrap is generated, and the most common reasons for non-conformance. This helps users build a prioritized roadmap for improving and retaining quality standards. This also reduces the cost of producing high-quality parts, such as scrap material, and lost labor hours. For medical device manufacturing in particular, there may be a higher cost of quality incurred due to pricing flexibility.

With production data contextualized with quality data, quality managers and continuous improvement teams can optimize their approach to quality management by:

Tracking work standards and procedures for an accurate benchmark of setup, changeover, and cycle time, which can be automatically updated in key systems, such as ERP.
Tying shop floor production runs to operational data for completion of operations.
Initiating automated workflows and notifications when downtime or non-conformance is detected to notify key personnel, such as quality managers.
Keeping an accurate history of quality data to benchmark scrap rate and retain a clear record of non-conformance.

Conclusion

AWS and MachineMetrics provide customers with the capabilities necessary to meet their regulatory, quality, and privacy requirements. Under the shared responsibility model, customers can use security features and tools to ensure that their applications and sensitive data are secured. At the same time, AWS will handle the undifferentiated heavy lifting of managing the cloud infrastructure. MachineMetrics uses AWS so their services run in a secure and stable environment.

MachineMetrics is dedicated to helping HCLS industry customers accelerate delivery for the next generation of manufactured products in a way that does not impede a customer’s regulatory quality manufacturing requirements, such as good manufacturing practices (GMP), ISO 13485, and 9001:2025. Working with MachineMetrics, customers can ensure that they are using data in a way that can best support their regulatory needs.

Medical device manufacturers can quickly prove out the value of an advanced production monitoring platform by deploying the MachineMetrics free trial program. Users can validate the ease of machine connectivity and generate a data-backed case for deploying across an entire facility. Contact us with further questions about MachineMetrics solutions and how they are applied in regulated manufacturing of medical devices.

MachineMetrics resources:

AWS blogs and resources:

1 – A metric used to assess how the people, processes, and machines/devices are operating on the manufacturing floor.

Related resource:
AWS cloud computing for manufacturing industry