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Each of these issues directly affects operational expenditure, leaving both margin and profit at risk. Under pressure to ensure the end price for the consumer remains competitive, the only logical course of action is for manufacturers to safeguard margin by lowering operational costs through eliminating inefficiencies.
In the early nineties there was an influx in ERP implementations, and companies invested in rolling out SAP or other ERP systems to standardise their business processes. Huge progress was made, however, the world has shifted again and the market demands more. Operational efficiency can no longer be improved by simply optimising mechanics alone. Your machinery needs to be connecting to smart sensors, gathering and analysing big data sets, and allowing you to make agile business decisions with the resulting insights.
What’s the next step?
Manufacturing Operations Transformation (MOT) is the continuation of transformation activities that aligns these manufacturing IT systems across the business to provide both operational and business improvement. According to McKinsey, the new industrial revolution has data at its very core and digital manufacturing technologies will transform every link in the manufacturing value chain, from research and development, supply chain and factory operations, to marketing, sales and service.
By digitising operational processes, manufacturers can connect operational goals with energy performance; they can then create the same (or greater) outputs with more efficient energy use, as well as easily and cost-effectively installing sensors on their devices. Then, by monitoring the energy profiles or machinery and systems, they can make the switch from reactive to predictive maintenance, maximise energy savings and increase Overall Equipment Effectiveness (OEE) and reliability.
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 reviewed on an ad hoc basis, and was therefore only 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 the calculation, contextualisation and storage of operational Key Performance Indicator (KPI) metrics.
This enabled the manufacturer to access real-time management dashboards, allowing them to monitor energy consumption in the context of each site, line and operator. This allowed them to isolate previously unidentified spikes in consumption and immediately take action to resolve them.
The true impact of IIoT is finding meaningful business context for your industrial data, and delivering actionable information for the business. This is especially true for manufacturers, who not only face a fight for survival from external challenges and competitors, but can often be up against other locations and plants within the same company which enjoy lower cost bases.
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