Actenum's blog articles

For most realistic real world situations, optimality is neither achievable nor desirable [1].

We're working on a proper architectural framework for planning and scheduling in production organizations. It provides a coherent process approach for the various activities and time horizons related to planning and scheduling, and also serves as a basis for the use of our technology solutions.

Technology is a key enabler of performance. Production organizations use a host of software systems to manage their operations: these include various implementations of Manufacturing Execution Systems (MES), Computerized Maintenance Management Systems (CMMS), Enterprise Asset Management (EAM) systems, and Asset Performance Management (APM) systems. At the same time, organizations are seeking ways to take the next step—to extend these technologies to optimize operational performance and automate operational decision-making. Until recently, however, suitable technologies were not available.

After attending the Intelligent Energy Conference in Amsterdam last February, I was struck by Karl Jeffrey’s Letter from the Editor in the April/May 2008 issue of Digital Energy Journal. Much of what he says in “Please can we call this IT again?” is accurate.

Canada has the longest coastline of any country in the world (243,042 kilometres/151,019 miles) and insufficient means to guard it all. Maintaining a presence in the Arctic, and providing security along the coast, is a challenge (some would call it a nightmare): tasks include providing surveillance, relief for vessels in distress, security management for events (such as the upcoming 2010 Winter Olympics in Vancouver), responding to natural disasters, and search and rescue.

I’ve written about the Perfect Plant concept before, after digging into it at last year’s SAP Adaptive Manufacturing Summit.

Earlier this month I was at Carnegie Mellon University attending the Center for Advanced Process Decision-making (CAPD) Annual Review Meeting, at the kind invitation of Professor Ignacio Grossman. CAPD brings together industry practitioners (primarily from process industry organizations) and academia, and harnesses a lot of brain power to work on some tough industrial optimization and process systems challenges.

Engineers and other knowledge workers have many software tools that help them become more productive and do better work, including various ways of mining, abstracting, and visualizing data. There are, however, many areas where the E&P industry could do much more to empower their knowledge workers and increase their productivity. An important example is the process of decision making.

In my previous post, I referred to “disruption management”. The application of disruption management techniques can use decision support software and analytic methods to cope with the impact of disruptions on a plan, a schedule, or an operational system.

According to the January 2008 edition of the Energy Insights Insights on Oil & Gas Newsletter, “[The] Pressure is on to increase recovery rates from known reserves given the expense of exploration.” And, “The Digital Oil field will see continued growth with enhanced production optimization.” In response, the authors state, “Oil and gas companies will look to tools for project and portfolio management, especially analytics that are able to support optimization.”