We’ve all heard about it, but what is big data and how does it impact you in the manufacturing industry?
Big data is a an extremely large set of data that can be structured or unstructured. It is an umbrella term used to describe any data set that is so large or complex that it requires innovative handling for analysis. The insights derived from big data analysis can enhance decision-making.
Big data is making a major impact on businesses, not least in manufacturing.
What does big data mean for manufacturing?
In manufacturing, big data originates from two general sources. Firstly, unstructured data from external sources such as the Internet and media. Secondly, data produced directly from the manufacturing process.
Huge volumes of data are at your fingertips, but it can only be truly put work if it can be automatically analysed.
In a sector that requires immediate problem resolution to maintain quality and productivity, it is essential that big data is structured. Maintaining structure means your data can be effectively and statistically analysed, and automatic calculations can be carried out.
Using big data to advance manufacturing
Structuring big data means you can effectively monitor it. All processes that need viewing and measuring can be displayed in a dashboard, making quality checks more efficient.
This means two things. The operator can monitor the quality of results and capability indices, and thereby maintain stability and consistency. Simultaneously, process engineers can be alerted if something is abnormal and correct the fault sooner than if they were relying on manpower or manual processes.
For example, in the automotive industry – in which mass production is typical – a small problem anywhere in the manufacturing process could snowball into quality issues in multiple end products. Big data offers a feasible solution to this.
Big data challenges
Big data is not without its challenges, especially as it is a relatively new and evolving discipline.
Sometimes the sheer size of a data set means that it can’t easily be measured fully. Also, variety can present a major challenge. Gaps can arise when you have multiple different systems with no standardised method for incorporating all the collected data.
Security can pose a challenge when engaging with big data. Different companies and countries have diverse practices and regulations for data security. A private cloud enables you to tailor the architecture to suit your needs and gives you the confidence that your data is stored completely within your organisation. A public cloud offers an enterprise-class firewall, the security expertise of your supplier and protection from hardware failure. Organisations need to evaluate whether a public or private cloud is better suited to their requirements.
Despite such challenges, big data will inevitably grow – as a phenomenon, as a process and as a business activity. For you in manufacturing, it will evolve to be a source of business benefits and opportunities that can’t be missed.
Utilising big data is the starting point for achieving a more connected and informed system to drive quality and productivity.
In the next blog of this series, we will explore the internet of things and the opportunities it presents for smarter, more connected factories.