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Streamlining the Chaos: Conquering Manufacturing With Data

The Complexity of Modern Manufacturing

Manufacturing today is far from the straightforward assembly lines of the past; it is chaos incarnate. Each stage in the manufacturing process comes with its own set of data points. Raw materials, production schedules, machine operations, quality control, and logistics all generate vast amounts of data, and managing this data effectively can be the difference between smooth operations and a breakdown in the process.

Data integration is a powerful way to conquer the chaos of modern manufacturing. It’s the process of combining data from diverse sources into a unified view, providing a holistic picture of the entire manufacturing process. This involves collecting data from various systems, such as Enterprise Resource Planning (ERP) systems, Manufacturing Execution Systems (MES), and Internet of Things (IoT) devices. When this data is integrated and analyzed cohesively, it can lead to significant improvements in efficiency, decision-making, and overall productivity.

The Power of a Unified Data Platform

A robust data platform is essential for effective data integration and should encompass analytics, data warehousing, and seamless integration capabilities. Let’s break down these components and see how they contribute to conquering the manufacturing chaos.

1. Analytics: Turning Data into Insights

Data without analysis is like raw material without a blueprint. Advanced analytics tools can sift through the vast amounts of data generated in manufacturing, identifying patterns and trends that might otherwise go unnoticed. Predictive analytics, for example, can forecast equipment failures before they happen, allowing for proactive maintenance and reducing downtime.

Analytics can also optimize production schedules by analyzing historical data and predicting future demand. This ensures that resources are allocated efficiently, minimizing waste and maximizing output. Additionally, quality control can be enhanced by analyzing data from different stages of the production process, identifying defects early, and implementing corrective measures.

2. Data Warehousing: A Central Repository

A data warehouse serves as a central repository where integrated data is stored. This centralized approach ensures that all relevant data is easily accessible, enabling comprehensive analysis and reporting. In manufacturing, a data warehouse can consolidate information from various departments, providing a single source of truth.

For instance, production data, inventory levels, and sales forecasts can be stored in the data warehouse. This unified view allows manufacturers to make informed decisions based on real-time data. If there’s a sudden spike in demand, the data warehouse can provide insights into inventory levels, production capacity, and lead times, enabling quick adjustments to meet the demand.

 3. Integration: Bridging the Gaps

Integration is the linchpin that holds everything together. It involves connecting various data sources and ensuring data flows seamlessly between them. In a manufacturing setting, integration can connect systems like ERP, MES, and Customer Relationship Management (CRM), creating a cohesive data ecosystem.

For example, integrating ERP and MES systems can provide a real-time view of production status, inventory levels, and order fulfillment. This integration eliminates data silos, ensuring that everyone in the organization has access to the same accurate information. It also streamlines workflows, as data doesn’t need to be manually transferred between systems, reducing the risk of errors and saving time.

Case Study: Aeriz

Aeriz is a national aeroponic cannabis brand that provides patients and enthusiasts with the purest tasting, burning, and feeling cultivated cannabis. They needed to be able to connect, manage, and analyze data from several systems, both on-premises and in the cloud, and access data that was not easy to gather from their primary tracking system.

By leveraging the Actian Data Platform, Aeriz was able to access data that wasn’t part of the canned reports provided by their third-party vendors. They were able to easily aggregate this data with Salesforce to improve inventory visibility and accelerate their order-to-cash timeline.

The result was an 80%-time savings of a full-time employee responsible for locating and aggregating data for business reporting. Aeriz can now focus resources on analyzing data to find improvements and efficiencies to accommodate rapid growth.

The Actian Data Platform for Manufacturing

Imagine having the ability to foresee equipment failures before they happen? Or being able to adjust production lines based on live demand forecasts? Enter the Actian Data Platform, a powerhouse designed to tackle the complexities of manufacturing data head-on. The Actian Data Platform transforms your raw data into actionable intelligence, empowering manufacturers to make smarter, faster decisions.

But it doesn’t stop there. The Actian Data Platform’s robust data warehousing capabilities ensure that all your critical data is centralized, accessible, and ready for deep analysis. Coupled with seamless integration features, this platform breaks down data silos and ensures a cohesive flow of information across all your systems. From the shop floor to the executive suite, everyone operates with the same up-to-date information, fostering collaboration and efficiency like never before. With Actian, chaos turns to clarity and complexity becomes a competitive advantage.

Embracing the Future of Manufacturing

Imagine analytics that predict the future, a data warehouse that’s your lone source of truth, and integration that connects it all seamlessly. This isn’t just about managing chaos—it’s about turning data into a well-choreographed dance of efficiency and productivity. By embracing the power of data, you can watch your manufacturing operations transform into a precision machine that’s ready to conquer any challenge!

The post Streamlining the Chaos: Conquering Manufacturing With Data appeared first on Actian.


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Author: Kasey Nolan

Is Your Data Management Strategy Ready for the Future of Manufacturing?

In the rapidly evolving landscape of the manufacturing industry, data has become a cornerstone of innovation. From robotics and connected factories to operational efficiency, the potential for leveraging data is boundless. However, to harness the full power of data, manufacturers must ensure that their data management strategies are not only current but also future-ready. For this reason, organizations must consider critical needs when creating a robust data management strategy. They must ensure that this strategy aligns with manufacturing priorities and carefully consider the value of digital transformation.

Defining the Manufacturing Data Management Strategy

A data management strategy is the backbone of successful data utilization in manufacturing. It encompasses the integration, standardization, and secure data storage, ensuring it is governed and trusted. In the context of the future of manufacturing, this strategy must align seamlessly with industry priorities, such as enhancing efficiency, maintaining quality control, predicting delays, and fostering innovation while simultaneously reducing costs.

The Role of Data Strategy in Digital Transformation for Manufacturing

A forward-thinking data management strategy is indispensable for any manufacturer looking to embark on a digital transformation journey. As the manufacturing landscape becomes increasingly digital and automated, selecting the right platform is crucial. A well-crafted data strategy, as often stated, is at the center of every successful digital transformation. This ensures not just immediate gains but also future-proofs the business against evolving technological landscapes.

Technology is a catalyst for digital transformation in manufacturing, enhancing efficiency, agility, and innovation. Integrating advanced technologies empowers manufacturers to optimize processes, improve product quality, and respond more effectively to market demands. By leveraging technology, manufacturers can not only optimize operations but also get ahead of any disruptions to suppliers or supply chains.

Key Metrics for Measuring Manufacturing Digital Transformation

Measuring the success of digital transformation in manufacturing requires defined metrics that should be an integral part of any data management strategy. These metrics serve as benchmarks, allowing manufacturers to gauge the impact of their digital initiatives. According to Gartner, “36% of manufacturing enterprises realize above-average business value from IT spending in digitalization at a reasonable cost compared with peers.”

Other metrics to consider include:

Customer Engagement

Track metrics such as website traffic, social media interactions, and customer feedback to assess the level of engagement with digital platforms.

Customer Satisfaction (CSAT) Scores:

Use surveys and feedback mechanisms to measure customer satisfaction with digital services, products, and overall experiences.

Operational Efficiency

Assess improvements in operational efficiency through metrics like reduced process cycle times, decreased manual intervention, and streamlined workflows.

Employee Productivity:

Monitor changes in employee productivity resulting from digital tools and automation. This can include metrics like tasks completed per hour or efficiency gains in specific processes.

Cost Reduction:

Measure the cost savings achieved through digital optimization, such as reduced manual processes, lower maintenance costs, and improved resource utilization.

Data Quality and Accuracy:

Evaluate the quality and accuracy of data, ensuring that digital transformation initiatives contribute to improved data integrity.

Customer Lifetime Value (CLV):

Evaluate the long-term value generated from each customer, factoring in repeat business, upsells, and customer loyalty influenced by digital initiatives.

Net Promoter Score (NPS):

Measure the likelihood of customers recommending your products or services as an indicator of overall satisfaction and loyalty.

Contextualized Data in the Fourth Industrial Revolution

Industry 4.0 represents a paradigm shift in manufacturing, characterized by integrating advanced technologies, digitalization, and data-driven decision-making. Entering the era of Industry 4.0 necessitates manufacturers to have clear, concise, and contextualized data.

Real-time decision-making is a cornerstone of Industry 4.0, and clear data ensures that manufacturers can swiftly respond to dynamic conditions, optimize processes, and troubleshoot issues in real-time. Predictive maintenance, a key aspect of this industrial revolution, relies on contextualized data to anticipate equipment needs and minimize downtime. By harnessing clear and contextualized data, manufacturers can optimize production processes, implement robust quality control measures, and achieve end-to-end visibility in the supply chain. This level of data clarity facilitates customization and personalization in production, enhances energy efficiency, and supports the integration of connected ecosystems within the manufacturing environment.

Additionally, manufacturers can identify potential risks through clear data insights and implement strategies to mitigate uncertainties. Clear data is crucial for ensuring compliance with regulatory standards, a necessity in Industry 4.0, given the increasing focus on stringent regulations.

Actian’s Role in Manufacturing Data Management

Actian has decades of experience helping manufacturers create and implement robust data management strategies. Actian’s solutions enable data-driven decision-making processes, ensuring manufacturers not only stay competitive in the present but also remain agile and prepared for the future.

In the dynamic landscape of manufacturing, a well-crafted data management strategy is not just a necessity, it’s a roadmap to success. As the industry hurdles towards an era of unprecedented technological advancement, manufacturers must ensure their strategies are not only current but also forward-looking. It’s time to embrace the future of manufacturing by putting data at the forefront of operations, and Actian is here to guide that transformative journey. Start a free trial now.

The post Is Your Data Management Strategy Ready for the Future of Manufacturing? appeared first on Actian.


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Author: Traci Curran

The Future of Automation in Manufacturing

As manufacturers know, automation enables a range of high-value benefits, such as cost and time savings. The Outlook of Automation in 2023 from Thomas Insights captures these advantages succinctly by noting that “automation promises lower operating costs, improved worker safety, a higher return on investment (ROI), better product quality, operational efficiencies, and competitive advantage.”

While automation isn’t new, manufacturers have been automating processes for decades as opportunities to expand it into new areas of the factory floor continue to emerge. Meanwhile, customizing and modernizing automation to fit a manufacturer’s unique needs can bring additional benefits, such as filling the gap caused by a labor shortage, making manufacturing processes more efficient, and meeting the changing needs of contract and original equipment manufacturing.

As automation continues to shape the future of manufacturing, automating data-driven processes will likewise make growing volumes of data readily available to support manufacturing use cases. The data can also make existing manufacturing processes more efficient and potentially more sustainable.

Automation in Modern Factories Comes in Many Varieties

Manufacturers see automation as a priority area for investing. According to a Deloitte survey, 62% of large companies plan to invest in robotics and automation, making it the top focus. The next highest area of investment is data analytics at 60%.

Digital transformations, which have swept through almost every industry, have helped lay the groundwork for the future of automation. In fact, according to a survey by McKinsey, 94% of respondents said digital solutions will be important to their future automation efforts. Other key technologies that are enabling the future of automation, according to McKinsey, include soft programmable logic controllers, digital twins, and teach-less robotics.

Most people probably immediately think of robotics when they think of automation in manufacturing. While the use of robotics has certainly advanced the industry, automation also extends into areas that many people don’t see.

For example, I’ve worked on projects that were as straightforward as transitioning from paper-based processes and manual entries on a computer to automating digital workflows that didn’t require human intervention. This type of project delivers time and money savings, and transparency into processes, even though it’s not as visible as a robotic arm on a factory floor.

Automating Both Data and Manufacturing Processes

Traditionally, automation has played a key role in manufacturers’ process controls. This includes supporting quality assurance processes, identifying risks, and predicting outcomes. The driving force for all of this automation at an enterprise level, not surprisingly, is data. However, getting a consolidated and normalized view of data is challenging. It requires a modern data platform that offers data warehousing and integration capabilities that bring together data from all needed sources and automates data pipelines.

The more disparate that the application landscape, ecosystem, and infrastructure become for manufacturers, the more they are going to need efficient and scalable data preparation and management capabilities. Legacy technologies and outdated processes that still require a lot of manual intervention will delay insights and are not scalable.

One proven way to solve this challenge is to use a small footprint, low maintenance, high performance database management system like Actian Zen. It can be embedded as part of an Internet of Things (IoT) strategy to advance manufacturing operations, including automation. With Actian Zen, manufacturers can also reap the benefits of edge applications and devices, which enable data-driven improvements all the way down to the process controller level.

Performing analytics at the edge and transmitting the results, rather than moving the entire data set to a data warehouse or platform for analysis, avoids the task of transferring data. This is certainly a big advantage, especially when manufacturers are faced with large data volumes, limited bandwidth, and latency issues.

For example, Actian is currently setting up a proof of concept to intercept data streams from a satellite that was shot up by a space organization that tracks GPS data from endangered animals. There’s a big problem with poaching for these animals, but if we can monitor their GPS movements, we can detect and then alert authorities when there are anomalies. This type of capability can help manufacturers pinpoint potential problems in automation by recognizing patterns or behaviors that deviate from a baseline.

A lot of IT applications require 5G or Global System for Mobile Communications (GSM), but these options have limited bandwidth. That’s why smart driving vehicles have not taken off—the bandwidth doesn’t support the vehicles’ massive data needs. Once the bandwidth improves to move data at the speed required for data-intensive applications, companies across all industries can find new use cases for automation in everything from manufacturing to the automotive industry.

Keeping Assembly Line Belts Moving Efficiently

Automation and digital transformations often go hand in hand to drive process and operational improvements across manufacturing. “Organizations are now utilizing automation as their most up-to-date approach for innovating and operating,” according to Smartbridge. “Companies are putting automation at the forefront of their digital strategies, making it a core priority for the entire enterprise.”

Similarly, Boston Consulting Group calls digitization and automation core elements of the “factory of the future.” Part of the reason is because manual processes are not designed for automation. Digital processes are, so they lend themselves to automating key aspects of supply chains, manufacturing tasks, and other operations. For example, manufacturers need to ensure they have enough supplies on-premises to keep their assembly line belts moving efficiently, but without incurring bloated inventory that increases storage costs. This is all in the interest of keeping production moving while minimizing costs, and nowadays meeting sustainability goals.

Accurately predicting and meeting rolling forecasts is the holy grail in manufacturing. Rolling forecasts are continuously updated based on past performance, current trends and operations, and other factors. Automating data processes to feed these forecasts gives stakeholders the real-time insights needed to make informed decisions that can impact all aspects of manufacturing.

Our customer Aeriz is a good example. The company unifies and analyzes data to inform a wide range of decisions. Aeriz is a national aeroponic cannabis brand, but it runs manufacturing processes that are reminiscent of those used by pharmaceutical companies. The organization’s leaders put a lot of thought into processes and automation controls, such as controlling the humidity and temperature for growing cannabis as well as the speed of conveyor belts for manufacturing processes. Like other companies, Aeriz relies on data to tell a comprehensive story about the state of the business and what is expected to happen next.

What this demonstrates is that the more opportunities there are to automate, from data processing to assembly line interactions, the more companies benefit from accuracy and time savings, which can transform standard operating procedures. Every step that can be automated provides value.

Improving Product Lifecycle Management

Bringing automation into manufacturing can solve new and ongoing challenges. This includes expanding the use of automation to optimize efficiencies, encourage sustainable operations, and make processes less complex. When the International Society of Automation (ISA) published a blog on the four biggest manufacturing automation trends of 2023, it called out connecting automation to sustainability goals, using automation to address skills shortages, leveraging automation as a competitive differentiator, and implementing more accessible forms of automation such as turnkey robotics.

These trends can certainly bring welcome advantages to manufacturing. Yet, from a big-picture view, one key benefit of automation is how it advances overall operations. When we think of manufacturing, whether it’s a mid-sized custom manufacturer or a large global enterprise, we oftentimes think of automating repetitive tasks. Once tasks are automated, it doesn’t mean the job is done. There may be opportunities to make changes, even minor enhancements, to improve individual processes or large-scale operations.

For example, manufacturers may find that they can further optimize the movement of a robotic arm to be faster or more efficient. Plus, connecting data from automated robotics with other sources across a factory floor may uncover ways to minimize waste, identify any silos or duplicated processes, and inform planning strategies. All of this ultimately plays a role in improving product lifecycle management, which can include everything from product design to testing and development. Improvements made to product lifecycle management can trickle down to improvements made on the factory floor.

Optimizing automation to drive the future of manufacturing requires not only an accurate overview of everything going on inside the factory walls, but also insight into what’s going on outside. This includes understanding supply chain operations and tier one, tier two, and tier three vendors. This helps ensure the manufacturer doesn’t run out of an essential item that can shut down production and bring automated processes to a halt.

The Future of Automation will Rely on Data

One aspect of modernization that’s been consistent over the decades—and is positioned to be the driving force into the future—is the use of data. As new use cases emerge, all available data will be needed to inform decisions and enable precision automation.

Manufacturers will need the ability to go from data source to decision with confidence. At Actian, we deliver by making data easy. We enable manufacturers and others to access unified, trusted data in real-time. The Actian Data Platform provides data integration, quality, and superior performance, along with native integration and codeless transformations that allow more users to access data to drive business goals.

With new capabilities such as integration as a service and database as a service, the Actian Data Platform meets the current and future needs of manufacturers. Find out what it can do for your business with a free 30-day trial.

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The post The Future of Automation in Manufacturing appeared first on Actian.


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Author: Robert Gorsuch