Big data covers every facet of our working life. Every aspect of pharmaceutical research and development involves the generation of huge quantities of data, with the expectation that we can turn this information rapidly into useful knowledge, which in turn can be used to make ‘data-driven’ decisions to better understand and control processes. This derived knowledge can also be used to reduce costs, improve efficiencies, reduce development times and facilitate rapid post-approval changes.
Year: 2018
One of the main challenges
to mineral processing plants is the efficient management of energy. Energy represents
a major cost in metals and mineral processing. The rising cost of energy has a
direct impact on the profitability of the operation, especially as the grade of
the ore is reduced over time. For example, in copper processing, comminution
uses over 50 percent of the total energy used to produce end product. As grade
decreases, the energy requirement and cost increases sharply, which
significantly reduces profit. Rising energy costs, economic volatility and climate
shifts are leading global corporations to adopt Energy Management Systems
(EnMS) to manage cost and comply with regulations. While initial energy
management systems may address localized conservation efforts, corporate
leaders are turning to recognized standards such as ISO50001 to accelerate
significant, enterprise-wide reductions in energy use.
Year: 2015
Increasingly, businesses of all kinds are beginning to see their data as an important asset that can help make their operations more effective and profitable. As our ability to gather time-series data grows, more technologies are becoming available to help us make sense of it. How do we choose the right technology and approach for our business problems? ...
Year: 2017
ARC Advisory Group looks at what Industrie 4.0 means for Covestro, a specialty polymers company, and other chemical companies.
Year: 2017
Manufacturing enterprises are ushering in a new era of digital industrialization, but many organizations are still failing to maximize the benefits of operational data. Instead, companies are overwhelmed by the volume and complexity of their real-time data and vital process information that could deliver operational insights is landlocked in multiple systems without necessary context to make informed decisions. OSIsoft’s Asset Framework (AF) – part of the PI Server – accelerates digital transformation by unifying disparate sources of data so individuals and organizations can gain insights to take action.
Year: 2017