OptPro White Papers

Downloadable case studies and best practices from the complex systems optimization experts at OptTek

Optimal Production Scheduling (OPS)

Commercial software offerings for production scheduling are rife with terms and labels suggest that there is a one-size-fits-all approach to production scheduling. Nothing could be farther from the truth. Learn how the technology behind OptPro can help truly optimize your production schedules by using models and approaches designed to optimize your specific operation.

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Digital Twins for Optimal Production Scheduling

Digital Twins have garnered much attention lately as trends like Industry 4.0, the Industrial Internet of Things (IIoT), and Smart Factories are coming into greater focus. However, the general perception seems to be that having a digital twin is expensive, usually entails large investments in all sorts of equipment sensors and controls, and usually requires more time and effort than it is worth for a manufacturing company.

In this paper, we will describe how OptProTM uses a digital twin to aid in optimal production scheduling (OPS), while we debunk a couple of myths about digital twins in this arena:

  1. That digital twins are too expensive for anyone other than the largest manufacturers to afford.
  2. That only processors with the most sophisticated ERP/MES systems – including equipment sensors and integrated process control systems – are able to make effective use of digital twins.
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Complex Production Scheduling: models, methods, and industry case studies

Manufacturing companies often employ processes that exhibit high levels of complexity, creating a need to identify optimal production schedules that can provide a source of competitive advantage. These companies typically operate in an environment where production costs represent a significant portion of the total product price, multiple products share manufacturing infrastructure and resources, and production schedules are required on a timely basis.

Seeing a gap as to solutions currently available in the marketplace, the PhD scientists at OptTek Systems developed OptPro, a sophisticated production scheduling solution approach that combines mathematical programming, metaheuristic optimization, and simulation to craft optimal or near-optimal production schedules in a reliable and effective manner.

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Tabu Search

Tabu Search, also called Adaptive Memory Programming, is a method for solving challenging optimization problems in the fields of business, engineering, economics and science. Everyday examples include practical applications in resource management, financial and investment planning, healthcare systems, energy and environmental policy, pattern classification, biotechnology and a host of other areas. Tabu search has emerged as one of the leading technologies for handling real-world problems that have proved difficult or impossible to solve with classical procedures.

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Metaheuristics

A metaheuristic is a high-level problem-independent algorithmic framework that provides a set of guidelines or strategies to develop heuristic optimization algorithms. Notable examples of metaheuristics include genetic/evolutionary algorithms, tabu search, simulated annealing, and ant colony optimization, although many more exist. Metaheuristics have been demonstrated by the scientific community to be a viable, and often superior, alternative to more traditional (exact) methods of mixed-integer optimization such as branch and bound and dynamic programming.

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Optimization in Supply Chain Planning and Management

The latest advancements in integrating optimization technology with evaluation techniques that model the complex supply chain environment have contributed to enabling improved and more focused decisions by the diverse set of managers involved in extracting the most value from the supply chain. OptTek Systems, Inc., a leading software and consulting services firm, offers state-of-the-art optimization solutions to address the most complex supply chain business problems.

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