For Manufacturing Companies, Success Lies in Tackling Data Management

Imagine being able to predict the future and reduce costs in your business, or prevent machine failures before they happen.  The ability to forecast hundreds of ways to improve your manufacturing business is now possible.  Information gathered from both machines and humans through automation technology and data exchange is redefining processes for every stage of production, to market delivery, and beyond.

The evolution of industry 4.0, a.k.a digital transformation in the manufacturing industry, has yielded a variety of technologies to help manufacturers improve quality, efficiency, and traceability. These include robotics, automation, smart sensors, manufacturing execution, and product lifecycle management software. These tools are augmented with wireless connectivity and sensors to monitor the entire production process and make autonomous decisions.

Harnessing High-Quality Data Collection Drives Competitive Advantage In Manufacturing

Manufacturing firms that master the collection and structuring of raw plant data into context for reporting, gain access to useful insights – insights that throttle them ahead of their competitors. The IDC estimates that manufacturing will be one of the top 3 industries where analytics will drive the largest growth for innovation adopters.  

In 2020, Tech Clarity released a report that included survey results of more than 300 manufacturing firms. They found that top performers in the manufacturing industry were at least two times more likely to have improved dramatically (more than 15%) over the past three years on a range of key performance indicators (KPIs). These KPIs included time to market, quality, and perfect orders. 

Top performers were also far more likely to improve dramatically on operational metrics, including yield, capacity utilization, and equipment availability. These top performers invested in automation, robotics, predictive analytics, and data management processes.  Entirely new levels of visibility are created when data from production operations is combined with operational data from ERP, supply chain, customer service, and other enterprise systems that were previously siloed.   

Once a manufacturing company has successfully orchestrated a functioning data management system, they gain the following competitive advantages:

• Downtime Reduction – Identification of equipment requiring maintenance before it breaks
• Prevent Incidents – Safety issue identification of safety issues before incidents occur such as  analytics could predict gas or chemical leaks and kick off a notification or warning system
• Waste Reduction – Quality deviations recognized prior to shipping out defective products or identifying waste reduction opportunity
• Enhanced Raw Material Tracking – Improve traceability by recording product data from the raw materials stage to sales and distribution and ensure compliance requirements are met in real-time
• Root Cause Analysis – Find correlations between defects and temperature, or defects and time of day to identify root causes of quality deviations 
• Supply Chain – Better calculate the products for manufacture in a defined time range and forecast sales opportunities and identify in-demand products with realistic deliverability timelines 
• Maintenance Optimization – Enhance operational prediction for machines and prevent downtime for machines that break or require repairs
• Risk Management – Use data to determine recurring errors or repetitive losses
• Logistics Automation – Measure product progress and development timelines for a clear production roadmap
• Product Development – Better understand consumer behavior, optimize product launches and features estimations
• Sales – Better understand the real price of products from the cost of materials, operations, machines, and tools purchased for manufacturing

Characteristics of Smart Manufacturing: Cooperation Between IT and OT

To make these data management systems and advanced analytics a reality, manufacturing firms must focus on restructuring IT teams.  Investing in the right data collection systems and evolving  IT infrastructure is a must to manage the increased volume of big data sets. 

It is impossible to implement a successful manufacturing analytics program without collaboration between IT and operational technology (OT) teams. Tech Clarity’s survey found that top-performing manufacturing companies are three times as likely to have achieved integration between IT and OT teams. They are also three times as likely to provide plant data access fast enough to impact performance. These two teams must come together and learn about each other’s worlds in order to boost plant productivity, product quality, and efficiency. Together, manufacturing IT and OT teams need to tackle:

• Increasing the speed of data delivery from plants to a data warehouse
• Find consensus on a single source of truth for making decisions
• Integrate their teams, whether this means combining them or designating liaisons
• Put data into a common context for analysis

Without tackling these challenges, manufacturing companies won’t be able to take advantage of the predictive analytics or real-time analytics that can give them a competitive edge.

Invest In IT Architecture To Meet Manufacturers’ Current and Future Technology Needs 

When building an IT infrastructure model to handle increasing volumes of data, manufacturing businesses are turning to the flexibility afforded by colocation as a foundational part of their hybrid IT strategy.  Here are some top benefits that colocation data center services afford:

1. Connected Colocation & Cloud Compute Environments Offer Savings With Flexibility

A key component in digital transformation for manufacturing requires building a hybrid multicloud IT infrastructure. Hybrid multicloud blends two or more public and private clouds to manage their computing workloads across cloud environments and colocation. Businesses can cost-effectively match workloads to the best deployment model for their organization as some environments are better suited for certain workloads – safely storing sensitive data in a colocation data center and less sensitive applications on cloud platforms.  Colocation also increases savings through direct on-ramps to cloud infrastructures, reducing costly egress fees. 

2. Low-Latency Connectivity

Plant managers can only make decisions in time to impact performance if data is collected and analyzed in real-time. Factory sensors continuously generate high volumes of data at a high velocity. Processing this data quickly requires low-latency network connectivity and proximity to data sources. 

This is where edge colocation providers can make a significant impact. Colocation affords manufacturers to house servers in secure and highly redundant data centers near factories to minimize latency, network disruptions, and reduce the risk of bandwidth strain or outages. Colocation providers also enable manufacturing companies to connect their edge deployments in multiple locations, which is ideal for companies that plan to have more than one factory or support geographically dispersed markets. 

Most colocation providers are well equipped to meet greater connectivity requirements, offering access to a competitive marketplace of network providers within their data centers. Tenants have multiple providers to choose from, so they can choose the one that best meets their business goals. Colocation data centers also have redundancy built into their networks with dual fiber pathways into the building to further increase network resilience.

3. High Compute Density

Rack densities have been rising steadily for years. However new technologies such as advanced analytics, robotics, and digital twins are data-crunching technologies that require much higher power densities.  Packing more compute into each piece of equipment means that electricity usage rises as well as the heat in each cabinet.  The current trend for HPC/Ai servers can draw 20-40kW per rack, requiring more advanced cooling at scale. Partnering with a colocation data center provider can deliver the concentrated power and cooling necessary to meet these demands.  

Additionally, high-density edge data centers allow manufacturers to provide video streaming and VR-based training for factory workers. Reduced streaming latency makes onsite VR-based training possible. 

4. Scale IT Infrastructure Faster and Cheaper

Building and maintaining multiple data centers to meet business is expensive and cost-prohibitive for most businesses. With a colocation provider, manufacturers have flexible space, and they only have to lease what they need. Monthly expenses don’t unexpectedly increase as they do with public cloud providers so manufacturing businesses often include colocation in their hybrid IT strategy for budget optimization of workloads that are better hosted in a secure environment where control and access is retained.

Colocation data center tenants also don’t have to spend money maintaining and modernizing the data center or worrying about out-growing their investment. With a continued focus on digital transformation, a trusted colocation partnership is a foundational element for growing businesses in the manufacturing industry. Safely storing, managing, and analyzing data requires flexible space that is difficult to replicate in-house, but much easier to keep pace utilizing colocation.

Element Critical supports smart manufacturers with high-density data centers in Houston, Austin, Chicago, Tyson’s Corner, and Sunnyvale. We guarantee 100% uptime, and we provide tailored infrastructure solutions that support our customers’ sustainability goals and make their visions for digital transformation a reality.   

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