VirtECS is a powerful tool for managing the timeline of any business. VirtECS adds considerable value to investments in data systems because it provides a way of organizing and integrating data in a goal-oriented way. VirtECS can be used to perform sensitivity analysis to determine which data is most important. In this way VirtECS can help to cut data costs by allowing companies to focus attention on data that matters the most. VirtECS can also help companies get the most out of process improvement methodology, such as Six Sigma approaches, because VirtECS models can be used to predict the bottom-line impact of proposed improvements. Process improvement effort can be avoided when a bottleneck is not impacted and the impact of variability can be assessed to determine how bottlenecks dynamically shift in response to variability.
The technology underlying VirtECS represents a revolutionary advance in optimizing process performance. For example, VirtECS has a revolutionary mathematical solver that has been designed to address the complex nature of the problems that are intrinsic to optimizing process performance and that stymie older technologies. Its mathematical capabilities enable VirtECS to provide intuitive insight into how to accommodate many choices, uncertainty, and variability. In fact, VirtECS was designed from the ground up to comprehensively optimize process behavior over time, support the understanding of process physics with easy to use mathematics behind the scenes, and to embody a constraint-based approach to improving performance. The VirtECS Resource Task Network (RTN) framework can describe any real-world manufacturing process and provides structure to data from Enterprise Requirements Planning (ERP) systems, Manufacturing Execution Systems (MES), and process historians. The VirtECS solver was designed from the ground up to work seamlessly with the RTN framework to automatically handle real world processes and provide users intuitive control to influence answers when needed.
VirtECS Augmented Intelligence
If you are a person curious to understand AI and have encountered marketing material and articles referencing its power, you should note that VirtECS makes heavy use of AI. In particular, APCI has used AI since its inception in 1993. However, the approach that APCI took was to use Augmented Intelligence – a futuristic variation of classical, and single mental model, approaches to AI. The key APCI assumption in taking this approach is that scheduling requires multiple mental models to be successful. Just as a human driving a car may use “muscle memory” most of the time to drive but when in bad weather or when someone darts across the road the driver relies on many other ways to think about what is occurring. For example, in bad weather the driver may remember that braking takes much longer, or even understand the changes in the coefficient of friction that take place, so they apply that knowledge to act accordingly. Along with mathematical programming and manufacturing process research, APCI has invested heavily in Augmented (Artificial) Intelligence (AI). In fact, APCI AI is its major defense against the NP-Complete nature of planning and scheduling problems, which results in mind-numbing complexity when seemingly small changes in a problem can result in dramatically different schedules or requiring even dramatically different approaches to solving the problems – ones that may not have even been invented yet.
VirtECS AI Was Designed to Expect to Learn and at an Increasing Rate
So, a natural question to ask is “What is APCI AI?”. The details of a complete answer are given in the “VirtECS Core Technical White Paper Series”. Intuitively the design of VirtECS expects that APCI will continuously learn about planning and scheduling applications and continually do new research on combinatorial optimization, manufacturing, and user interfaces for planning and scheduling. As such VirtECS was architected and expected to advance on a regular basis. This is made possible by layers of technology platforms, each of which is extensible and which consists of hundreds of mental models proven to be useful to planning and scheduling automation. For example, the infinite dimensional programming layer is based upon a collection of theorems and a waveform-based solver technology that is unique to APCI. As APCI continues to learn by exposure to real world applications, additional theorems and enhancements to the waveform-based solver technology occur occasionally and the infinite dimensional programming layer is designed to naturally accept a wide range of new knowledge. Experience over twenty-five years has shown that the theorem base has expanded by multiples and enabled the ability to focus computer cycles where they add the most value and accelerate performance. All the VirtECS layers expand according to the nature of the anticipated new knowledge and for this reason VirtECS is much faster today and in a way that lets VirtECS easily take advantage of much faster computers and much more computer memory. The VirtECS design was developed by surveying the global academic literature and the many approaches to scheduling and abstracting them to a layered platform with built-in means of being extended. This means VirtECS regularly advances and that VirtECS can be applied across many industries. APCI has noted over the years the occasional and often fleeting competitor in a given area, but never have one of these industry specific competitors appeared in more than one industry in which APCI operates. The other advantage of the APCI AI approach is that learning abstracted from one industry often applies to other industries meaning that VirtECS improves with each implementation in each area of APCI operation. As APCI expands to new industries there are new ways for existing customers to take advantage of the APCI AI learning. The bottom line is that APCI AI is not just what a computer can reason about, but what VirtECS plus hundreds of person years of advanced insight can become and placed into your hands to generate value.