Jamie Hinton, CEO and Co-founder of Razor, Explains How Tech Helps Bridge the Gap In Manufacturing
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.
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.
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.