DCN June 2016 - Page 22

Big Data & IoT ASSET ADVICE Andy Graham of SolutionsPT looks at the role of automation software and data analytics in unlocking hidden energy savings and increasing efficiency for manufacturers. T he challenges currently facing UK manufacturers have never been greater, with increasing price pressure, rising production energy costs, supply chain volatility and ever changing regulations having an impact. Each of these issues has a direct impact on operational expenditure, leaving margin and profit under threat. Under pressure to ensure the end price for the consumer remains the same – or lower – the only logical course of action is for manufacturers to safeguard or claw back margin by lowering operational costs through eliminating inefficiencies. Energy spend One area where manufacturers can look to make these much needed savings is in their energy spend. Becoming energy efficient provides manufacturers with a specific set of challenges, combining both regulatory and commercial considerations, meaning effective energy management is no longer an option; it’s a strategic business necessity and unlocking the hidden value of Big Data holds the key. ‘Big Data’ is the term given to a set of information so vast and complex that conventional database management tools or traditional data 22 processing applications are incapable of handling such huge volumes. An average manufacturing site readily generates tens of millions of data points every day and can require this data to be stored for many years. Despite having access to huge amounts of data, not all manufacturers are using it as strategically. Many companies have already invested in a data infrastructure but don’t realise the extent of the data they are currently collecting and how it could be analysed and applied for business improvement. Simply put, they have a huge data asset that they are not making the most of. In these harsh economic times, where the emphasis is on increasing productivity without increasing capital investment, it would make sense to squeeze as much benefit from this data asset as possible. So, how can we realise the potential of Big Data and make it work for energy management? Energy consumption in manufacturing facilities can be reduced by using the latest automated technologies, more efficient equipment and through improved monitoring and control of energy used in infrastructure. This software and data based approach is increasingly popular with UK manufacturers who have either exhausted other methods or find the cost to modernise their entire infrastructure prohibitive. For many, the prospect of a complete infrastructure upgrade is impractical but, through the implementation of Corporate Energy Management solutions, businesses can develop a stronger and more insightful understanding of their operations, and are able to visualise their energy use and see any inefficiencies. Used effectively, such solutions can allow operatives to monitor real time energy usage and automatically notify operators, supervisors and management of energy inefficiencies and waste. Information framework Recently, one of the largest beverage manufacturers in the world wanted to improve the way it monitored its energy usage. Smart metering theoretically allowed the company to track consumption but the data was stored in an isolated database and only ever reviewed on an ad hoc basis, so was therefore of limited use. As part of a pilot scheme, the company implemented Wonderware Intelligence, an Operational Intelligence (OI) product that creates an information framework to simultaneously connect to industrial data sources and to automate