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Razor Insights

How Tech Helps Bridge The Gap In Manufacturing

Written by Jamie Hinton
Published on
Jamie Hinton, CEO at Razor Ltd, tells us how manufacturing can harness digital transformation to ultimately reap the rewards of growth. Manufacturers need to embrace change and risk in order to stay competitive, whilst remembering that it’s not just about connecting devices, it’s about developing an environment in which humans and machines work seamlessly together to perform optimised processes

Manufacturing is an industry that harnesses technology in order to deliver on efficiency and productivity.

However, manufacturers are coming under increasing pressure to produce higher-quality goods, faster and at a lower cost. They are continuously looking at ways in which they can increase productivity, efficiency and effectiveness in order to increase profits and ensure long-term success.

Jamie Hinton, CEO at Razor Ltd, tells us how manufacturing can harness digital transformation to ultimately reap the rewards of growth.

“The industry is changing, and traditional, linear supply chains are needing to evolve into dynamic, interconnected systems. We are producing more data than ever before, and the evolution of technology has the ability to give manufacturers access to real-time data at every point during the process.

Manufacturing executives are beginning to acknowledge the importance of digital transformation, but only 30% have committed to investing in digital transformation, whilst 5% are satisfied with their current strategies.

Many manufacturers are clearly wary of embracing this new era, where technology is leading the way for fear that it has no clear value. However, we are seeing that the most successful manufacturers today, are the ones that are constantly evaluating their supply chains, and utilising new technology in order to do this more intelligently.

Other manufacturers may feel that implementing digital transformation can be an expensive investment, but it doesn’t have to be the case. Focus on taking small, incremental steps when it comes to accessing the tangible opportunities digital transformation can create. Think clearly about the kind of data and knowledge that would be of most value - this is where our Discovery process can help. It’s a framework that enables us to select the most effective tools and techniques for each Discovery that we conduct, during which we immerse our experts with you, your colleagues and your customers. Results can then be presented, before you make any final decisions on investment.

The advancements in technology provide manufacturers with opportunities to transform the workplace.

Innovations include mobility, cloud, advanced analytics, AI, wearables and VR devices, which can all be used to provide powerful productivity-enhancing capabilities throughout the supply chain.

The increasing digitisation of information has resulted in a complete explosion of data that can be utilised to improve production processes, achieve greater consistency and even create safer working environments. But in order to do so, manufacturers need to ensure that the appropriate infrastructure and robust integrations are in place.

For example, you can have a smart factory and a transformed business, but if you don’t have an innovation model that matches market needs, it’s not going to be profitable. Digitising the industry can result in lower production costs, quicker turnarounds and more efficiently meeting customer demands.

A machine’s ability to learn and adopt behaviour is not new, but it’s the advanced algorithms of today that are transforming the way in which the industry collects information and predicts behaviour. But we are fast entering an era where quality is no longer sacrificed for efficiency as algorithms determine the factors that impact production and improve accuracy and workflow.

Big data analytics is crucial for digital transformation in manufacturing.

In order to bridge the gap, manufacturers will need to ensure cloud-based infrastructures are implemented. Attempting to achieve big data analysis, storing and backing up huge data sets and deploying various facets of machine learning models in production in your own infrastructure, although not impossible, would be a huge distraction from delivering the value of the project.

One thing is clear, manufacturers need to embrace the change and risk in order to stay competitive, whilst remembering that it’s not just about connecting devices, it’s about developing an environment in which humans and machines work seamlessly together to perform optimised processes”