The complex industrial environment forces the manufacturing companies to improve often their production system during its whole life-cycle. The system can be optimized both from a design and operative point of view. To be competitive, companies need to perform quickly interventions on their production lines and, therefore, they are looking for advanced engineering approaches able to support fast decision making. The knowledge of how a production line works is a key factor for companies competitiveness. The accuracy and efficiency of analytical performance evaluation models could enable the integration of these methods in optimization algorithms. Traditionally, the optimization problems have been researched separately and various techniques have been used to solve them. However, these methods could be inefficient or unreliable. The objective of this thesis is to integrate the different optimization problems in a unique formulation and to propose a reliable and efficient method to solve it. This integrated approach would represent a novel contribution in the field of production line optimization. The complexity of the problem lies on non-linear and non-explicit relations between the performance functions of the system with respect to optimization parameters. The method that will be proposed in this dissertation exploits linear ap- proximations of the performance functions. From a geometric point of view, this means that a tangent hyperplane at a given point is used to approximate the performance curve. In this way, the optimization problem is converted to a linear programming problem, that can be solved with existing methods. The main effort of this thesis is dedicated to the analytical calculation of the tangent hyperplane. The proposed method is applied to two real-life cases, proving its industrial applicability and relevance.
Il complesso ambiente industriale spinge le aziende manifatturiere a migliorare spesso i loro sistemi produttivi durante tutto il loro ciclo vita. Il sistema può essere ottimizzato da un punto di vista progettuale o operativo. Per essere competitive, le aziende necessitano di compiere velocemente gli interventi sui loro sistemi di produzione e, quindi, cercano avanzati metodi ingegneristici capaci di supportare processi decisionali rapidi. La conoscenza di come una linea di produzione operi è un fattore fondamentale per la competitività aziendale. I metodi analitici, grazie alla loro accuratezza ed efficienza, potrebbero essere integrati in algoritmi di ottimizzazione. Tradizionalmente, i problemi di ottimizzazione sono stato studiati separatamente e varie tecniche sono state adottate per risolverli. Tuttavia, questi metodi potrebbero risultare inefficienti o inaccurati. L’obiettivo di questa tesi è di integrare i diversi problemi di ottimizzazione in un’unica formulazione e di proporre un metodo efficiente e affidabile per risolvere il problema così formulato. Questo approccio integrato è un contributo innovativo nella ottimizzazione delle linee di produzione. La complessità del problema giace in relazioni non-lineari e non-esplicite tra le funzioni di performance del sistema e i parametri di ottimizzazione. Il metodo che verrà proposto in questa tesi sfrutta approssimazioni lineari delle funzioni di performance. Da un punto di vista geometrico, un iperpiano tangente alla curva in un punto specifico verrà utilizzato per approssimare la funzione. In questo modo, il problema di ottimizzazione viene convertito in un problema di programmazione lineare, che può essere risolto facilmente con metodi esistenti. La tesi si concentra principalmente sul calcolo analitico dell’iperpiano tangente. Il metodo proposto verrà applicato a due casi reali in modo da mostrarne l’applicabilità e la rilevanza industriale.
An analytical tangent hyperplane method to support the design and operation of asynchronous production lines
ROSSIGNOLI, RICCARDO
2018/2019
Abstract
The complex industrial environment forces the manufacturing companies to improve often their production system during its whole life-cycle. The system can be optimized both from a design and operative point of view. To be competitive, companies need to perform quickly interventions on their production lines and, therefore, they are looking for advanced engineering approaches able to support fast decision making. The knowledge of how a production line works is a key factor for companies competitiveness. The accuracy and efficiency of analytical performance evaluation models could enable the integration of these methods in optimization algorithms. Traditionally, the optimization problems have been researched separately and various techniques have been used to solve them. However, these methods could be inefficient or unreliable. The objective of this thesis is to integrate the different optimization problems in a unique formulation and to propose a reliable and efficient method to solve it. This integrated approach would represent a novel contribution in the field of production line optimization. The complexity of the problem lies on non-linear and non-explicit relations between the performance functions of the system with respect to optimization parameters. The method that will be proposed in this dissertation exploits linear ap- proximations of the performance functions. From a geometric point of view, this means that a tangent hyperplane at a given point is used to approximate the performance curve. In this way, the optimization problem is converted to a linear programming problem, that can be solved with existing methods. The main effort of this thesis is dedicated to the analytical calculation of the tangent hyperplane. The proposed method is applied to two real-life cases, proving its industrial applicability and relevance.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/148773