Modelli simulativi per la progettazione di una linea di assemblaggio con operatori fissi o mobili

I metodi di organizzazione della produzione di una linea di assemblaggio con operatori fissi e con operatori mobili sono i più diffusi nell'ambito industriale. Il primo, quello tradizionale, è molto efficiente perché ogni stazione della linea ha il proprio operatore, il quale deve compiere solo l'operazione destinata a tale postazione. Il secondo, un metodo più recente, tenta di legare all'efficienza dell'operatore fisso anche la flessibilità che ne deriva da avere operatori che possono eseguire più task in diverse stazioni della linea. In questo documento verranno analizzate diverse linee di assemblaggio al variare di parametri caratteristici con operatori fissi o mobili grazie all'utilizzo di modelli simulativi. Successivamente i dati raccolti verranno analizzati per poter determinare quale dei due metodi è il più conveniente in una determinata situazione.The methods of organizing the production of an assembly line with fixed operators and with walking operators are the most widespread in the industrial sector. The first, the traditional one, is very efficient because each station on the line has its own operator, who only has to perform the operation intended for that station. The second, a more recent method, attempts to link the efficiency of the fixed operator to the flexibility that derives from having operators who can perform multiple tasks in different stations on the line. In this document, various assembly lines will be analyzed as the characteristic parameters change with fixed or mobile operators thanks to the use of simulation models. Next the collected data will be analyzed in order to determine which of the two methods is the most convenient in a given situation

Modello per la progettazione di linee di assemblaggio mixed-models: confronto tra fixed workers e walking workers

La tesi riporta l'implementazione di un modello tramite il software Matlab da utilizzare come supporto in sede di progettazione di una linea di assemblaggio mixed-models. Il modello restituisce, al variare di alcuni parametri, la configurazione più conveniente in termini di produttività tra il sistema ad operatori fissi (FW) e il sistema ad operatori mobili (WW). Per il confronto è stato impiegato in entrambi i casi lo stesso numero di operatori. I parametri analizzati sono stati: sbilanciamento dei tempi di assemblaggio nelle stazioni, tempo ciclo ideale, velocità di spostamento tra le stazioni, coefficiente di penalizzazione in termini di tempo per il sistema WW rispetto a quello FW, dimensione dei buffer interoperazionali

Manufacturing Management and Decision Support using Simulation-based Multi-Objective Optimisation

A majority of the established automotive manufacturers are under severe competitive pressure and their long term economic sustainability is threatened. In particular the transformation towards more CO2-efficient energy sources is a huge financial burden for an already investment capital intensive industry. In addition existing operations urgently need rapid improvement and even more critical is the development of highly productive, efficient and sustainable manufacturing solutions for new and updated products. Simultaneously, a number of severe drawbacks with current improvement methods for industrial production systems have been identified. In summary, variation is not considered sufficient with current analysis methods, tools used are insufficient for revealing enough knowledge to support decisions, procedures for finding optimal solutions are not considered, and information about bottlenecks is often required, but no accurate methods for the identification of bottlenecks are used in practice, because they do not normally generate any improvement actions. Current methods follow a trial-and-error pattern instead of a proactive approach. Decisions are often made directly on the basis of raw static historical data without an awareness of optimal alternatives and their effects. These issues could most likely lead to inadequate production solutions, low effectiveness, and high costs, resulting in poor competitiveness. In order to address the shortcomings of existing methods, a methodology and framework for manufacturing management decision support using simulation-based multi-objective optimisation is proposed. The framework incorporates modelling and the optimisation of production systems, costs, and sustainability. Decision support is created through the extraction of knowledge from optimised data. A novel method and algorithm for the detection of constraints and bottlenecks is proposed as part of the framework. This enables optimal improvement activities with ranking in order of importance can be sought. The new method can achieve a higher improvement rate, when applied to industrial improvement situations, compared to the well-established shifting bottleneck technique. A number of “laboratory” experiments and real-world industrial applications have been conducted in order to explore, develop, and verify the proposed framework. The identified gaps can be addressed with the proposed methodology. By using simulation-based methods, stochastic behaviour and variability is taken into account and knowledge for the creation of decision support is gathered through post-optimality analysis. Several conflicting objectives can be considered simultaneously through the application of multi-objective optimisation, while objectives related to running cost, investments and other sustainability parameters can be included through the use of the new cost and sustainability models introduced. Experiments and tests have been undertaken and have shown that the proposed framework can assist the creation of manufacturing management decision support and that such a methodology can contribute significantly to regaining profitability when applied within the automotive industry. It can be concluded that a proof-of-concept has been rigorously established for the application of the proposed framework on real-world industrial decision-making, in a manufacturing management context.Volvo Car Corporation, Sweden University of Skövde, Swede

Development of a cost reduction methodology for start-up SMES developing a novel product.

This thesis is concerned with identifying cost engineering requirements of start-up SMEs in the manufacturing sector and developing a solution to address a number of their major requirements. The focus of the thesis is on cost reduction at the product development stage of a novel product. The aim of the thesis is to develop a cost reduction framework for SMEs developing a novel product in order to transfer necessary cost engineering knowledge to an SME in a structured way. A literature review has been completed to identify potential areas for cost reduction and build an understanding of SMEs’ characteristics in cost engineering requirements. The review confirmed the finding that SMEs lack cost engineering knowledge. Therefore, cost reduction best practices were identified through literature review and analysed for relevance for SMEs. Collaborating with a start-up SME developing a novel product helped to identify SMEs cost engineering requirements. By close observation and participation of the SME, areas lacking knowledge were identified. In addition, potential cost reduction opportunities were examined. Due to the nature of cost reduction activities, it was required to study day to day activities of the collaborating company and become familiarised with development, production and business plans for the product. The identification of the requirements and development of the AS IS model of the SME helped to build an understanding of characteristics and requirements of start-up SMEs. Based on these the cost reduction framework was developed. The framework includes best practice tools and methods which comply with start-up SMEs’ characteristics. Where a suitable method could not be identified, the method was developed in this research to address their requirements. The framework was implemented in the collaborating company and was validated by presenting the results to internal and external experts from industry and academia. Keywords: Start-up SME, Cost Engineering, Manufacturing, Novel product, production cost.PhD in Manufacturin