Google & GFT: An Engine to Unlock the Power of Data

Manufacturing is undergoing profound transformation, driven in many ways by the power of AI. 

But for many companies, siloed data still stands in the way. 

Seeking to address this is Google Cloud and GFT, the global digital transformation partner.

They've been working together since 2019 to implement the digital infrastructure manufacturers need to better store, collate and analyse their data. 

Having this data clean, accessible and organised is crucial for successfully pursuing new AI use cases across the production lifecycle. 

Use cases which Google Cloud and GFT will be showcasing at MxD's (Manufacturing x Digital)’s innovation centre, providing a hands on perspective for manufacturers. 

Before we discuss this news however, there's critical context to address. Why is there still so much siloed data in manufacturing?

Siloed data: A major obstacle

Siloed data is a serious problem.

It restricts the flow of critical information across systems and departments, it blocks a holistic view of operations and its fragmentation interferes with analysing production processes, identifying bottlenecks and responding to issues swiftly. 

This creates a whole host of other problems further along the supply chain, where teams are unaware of delays or miss early warnings from machines, leading to unexpected downtime. 

Industry 4.0 technologies like AI overwhelmingly rely on large, diverse datasets. Even with technologies that don't necessarily need this data — like industrial robots, where you can program it to perform the same actions repeatedly — manufacturers miss out on newfound efficiencies and improvements from not having it available and analysing it. 

Most manufacturers are aware of these issues. So why does siloed data persist? 

It's down to overarching structural, technological and logistical factors.

These factors are a part of the historic foundation of manufacturing and will require consistent overhaul to address. 

The reasons Siloed data is still so prevalent 

• Legacy Systems

Manufacturers continue to rely on older, disconnected systems for inventory management, production planning and quality control. These systems were often designed in isolation and not built for interoperability, creating a system of fragmented data storage.

Upgrading these systems is a complicated and costly task, causing downtime and requiring investment that will impact profitability and operational success. For many their systems are doing the most important job — keeping the business operational — and doing this will be a huge issue. 

• Specialised Tools

Different departments, like maintenance, supply chain and production often use specialised software tailored to their specific functions which generates its own specific data.

These tools rarely easily integrate with each other, so data sharing across departments is rendered difficult. To combat this, manufacturers would have to find, oversee and require the use of software that can integrate seamlessly cross all these different departments, which is a challenging task. More platforms of this nature need to be available. 

• Cultural Barriers

Data silos are also being driven and deepened by organisational culture. Departments can be protective of their data or lack incentives to share information. Often the process of sharing takes too much time, impacting productivity. This ultimately leads to poor collaboration and hinders the creation of a unified data ecosystem.

• Data Security and Privacy

Data silos are also being driven by concerns over security and intellectual property protection. This is especially a big factor as it pertains to new technologies like AI, where legislation around creative ownership is murky at best. This contributes to the isolation. 

• Scale and Complexity

Siloed data also persists because of the sheer scale and complexity of manufacturing. Manufacturers have multiple plants which operate semi-autonomously, often using different, non-interconnected systems. 

Standardising data across locations takes a lot of work and time that could be spent being productive. As a result data is compartmentalised, making it harder for manufacturers to leverage its full potential. 

Something with GFT and Google Cloud are seeking to address. 

GFT & Google Cloud: A data-driven partnership

The new demonstration by GFT and Google Cloud will showcase real-life implementations of Google Cloud’s Manufacturing Data Engine (MDE).

This innovative cloud-based platform enables companies to analyse and store data from any machine across their factory floors. 

This subsequently places data into an easily accessible format, allowing manufacturers to leverage it for key AI, automation and machine learning applications. 

Examples of these applications that make factories fun smoother and more efficiently include predictive maintenance, production forecasting and quality control. 

Predictive maintenance relies on holistically reviewing real-time and historical data, which this platform enables. 

The same is true for production forecasting, which enables manufacturers to streamline production through data-driven insights. 

Data is also the primary ingredient in improving quality standard and consistency.

It takes the decision-making criteria from assumptions to hard facts, ensuring manufacturers make more accurate and impactful choices.

GFT has both contributed to the development of Manufacturing Data Engine, and successfully implemented it for a US automaker.

In addition to providing the necessary software expertise for implementations of MDE, GFT also works on the hardware for various sensors, cameras and machinery.

Both companies are excited about the opportunity to provide a scalable solution to manufacturers that helps them embrace data's true power. 

“With so many new AI capabilities available to them, many companies are working to determine which use cases to put their resources towards in order to have the most significant — and in some cases, the most immediate — impact on their manufacturing processes,” says Scott Hofmann, Chief Revenue Officer, U.S. at GFT.

“Our latest work with Google Cloud gives manufacturers  the tangible evidence they need to make these decisions, and then quickly execute on them.”

Fabien Duboeuf, Industry Manager, Manufacturing at Google Cloud, adds: “Together with GFT, we’re not only demonstrating how manufacturers can transform their data, but their entire factory operations from end to end.

“This showcase provides a hands-on demonstration, and how the art of the possible can be applied industry-wide to introduce a level of innovation, agility and efficiency required to meet customer’s expectations.”

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