Computation of energy efficient driving speeds in conveying systems

Windmann, Stefan; Niggemann, Oliver; Stichweh, Heiko

doi:10.1515/energyo.0127.00003

Cited by 2 publications

(1 citation statement)

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“…It also needs to handle the complexity of the production plant and therefore consider the system parametrization as well as the system topology simultaneously. A lot of research has been done on the dynamic optimization of the numeric parameters of a system [12,20,19]. However, most of these methods only work for a static system configuration and cannot adapt to varying demands.…”

Section: Reconfiguration After Faults Occurredmentioning

confidence: 99%

First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems

Diedrich

Balzereit

Niggemann

2020

Technologien Für Die Intelligente Automation

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Maintaining modern production machinery requires a significant amount of time and money. Still, plants suffer from expensive production stops and downtime due to faults within individual components. Often, plants are too complex and generate too much data to make manual analysis and diagnosis feasible. Instead, faults often occur unnoticed, resulting in a production stop. It is then the task of highly-skilled engineers to recognise and analyse symptoms and devise a diagnosis. Modern algorithms are more effective and help to detect and isolate faults faster and more precise, thus leading to increased plant availability and lower operating costs.In this paper we attempt to solve some of the described challenges. We describe a concept for an automated framework for hybrid cyberphysical production systems performing two distinct tasks: 1) fault diagnosis and 2) reconfiguration. For diagnosis, the inputs are connection and behaviour models of the components contained within the system and a model describing their causal dependencies. From this information the framework is able to automatically derive a diagnosis provided a set of known symptoms. Taking the output of the diagnosis as a foundation, the reconfiguration part generates a new configuration, which, if applicable, automatically recovers the plant from its faulty state and resumes production. The described concept is based on predicate logic, specifically Satisfiability-Modulo-Theory. The input models are transformed into logical predicates. These predicates are the input to an implementation of Reiter’s diagnosis algorithm, which identifies the minimum-cardinality diagnosis. Taking this diagnosis, a reconfiguration algorithm determines a possible, alternative control, if existing. Therefore the current system structure described by the connection and component models is analysed and alternative production plans are searched. If such an alternative plan exists, it is transmitted to the control of the system. Otherwise, an error that the system is not reconfigurable is returned.

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Section: Reconfiguration After Faults Occurredmentioning

confidence: 99%

First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems

Diedrich

Balzereit

Niggemann

2020

Technologien Für Die Intelligente Automation

Self Cite

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Model-based routing in flexible manufacturing systems

Windmann

Balzereit

Niggemann

2019

At - Automatisierungstechnik

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In this paper, a model-based routing approach for flexible manufacturing systems (FMS) with alternative routes for the work pieces is proposed. For each work piece, an individual task has to be accomplished, which consists of several processing steps. Each processing step can be executed on alternative working stations of the FMS. The proposed routing method employs a model of the conveying system to find energy efficient and fast routes for the respective work pieces. The conveying system model is based on a directed graph, where the individual conveyors are modeled as weighted edges. It can be straightforwardly applied to several types of FMS by adjusting the application-dependent parameters. Efficient computation of the fastest route through the conveying system is accomplished by means of dynamic programming, i. e., by integration of Dijkstra’s algorithm in a dynamic programming framework, which is based on the proposed conveying system model. Additional consideration of energy efficiency aspects leads to a Mixed Integer Quadratically Constraint Program (MIQCP), which is solved by substitution of Dijkstra’s algorithm by a branch and bound method. Experimental results for an application scenario, where the energy efficient routing method is applied to route work pieces between the working stations of an FMS, lead to 20 % reduction of energy consumption on average.

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Computation of energy efficient driving speeds in conveying systems

Cited by 2 publications

References 0 publications

First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems

First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems

Model-based routing in flexible manufacturing systems

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