Turin has long been a town in which almost all economic activities were finalized to the mass production of cars, while the choices of its economic developments depended on those of the car firm, Fiat. In the 1950s and 1960s, both Turinese industry and labour market were tightly organised by Fiat in a pyramid-like structure, at the top of which were the car company and its workers respectively. Fiat's efforts to 'rationalize' and control the local labour and components market were not accompanied by a similar strategy towards social structure. Fiat limited itself to supporting the conservative political parties in office in Turin, which were able to gain a stable consensus by Tuninese petty bourgeoisis, but were not far-sighted enough to try to integrate the immigrant workers through a policy of reforms and services. This turned out in a very conflictual pattern of industrial relations in the late 1960s. Thus, the economic crisis which hit the mass-production firms worldwide in the mid-1970s had particularly negative effects on Fiat, due to bitter industrial relations within the plants. Elsewhere, as the large mass-production firms did not recover from the crisis, the segmentation of product markets and the availability of the new electronically-based technologies, which allow a greater flexibility together with high levels of productivity, fostered the emergence of a new competitive model of industrial organization: flexible specialization. These very market and technological conditions, interacting with the local social dynamics, also helped a wide reorganization of Turinese industry which ceased to depend strictly on Fiat's choices and orders. At the same time, the social structure of Turin became much more differentiated and the strategies of social actors proved to be no longer as linked to Fiat's decisions as in the past. Instead, throughout the 1970s Fiat was unable to respond to the new conditions of competition and to undertake a deep process of restructuring, due to the unpreparedness of its own management and to the strict unions' control over its moves. Only once the unions had been defeated in 1980, Fiat was able to take the lead among European car makers in a few years in terms of sales, technology and market strategy. My dissertation tries, therefore, to answer to the following questions: how did it happen? And how did the mentioned endogenous and exogenous factors influence Fiat's strategy? How is the Turinese model of industrial organization at the present, and what is Fiat's role in it?

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Having been looking in to the subject of future truck interior environment, the first intention was to be inspired of the extreme environment of long haul-age truck driving and improving the user needs. By looking in to the human factors in truck interiors. I wanted to show the benefits of the truck architecture possibilities and recreate it for a new future truck user. By using the main design tools like design research, sketching, full scale projection and quick user testing I could get a quick look into the complexity of current truck driver environment and proceed with developing it further. The final result is a semi-autonomous truck interior that is suited for a new type of future driver. The interior is focused on the user needs and tasks such as; autonomous management of logistics, operating routes with other truck drivers and units, enjoying spare time while not driving and also the possibility to actively taking over the control manually in case of emergency. By separating and dividing the truck interior in different divisions and user modes, such as Operational, Tactical and Strategic, that divides the specific functions above, the architecture can maintain a clear separation between work and leisure for the driver when he or she is driving or not. This way the driver could easily switch between the modes to reduce the cognitive impact of increasing future information cognitive impact, without losing the sense of control and create a safe and comfortable work environment for herself. The concept is based on the knowledge of a flexible future context that is facing the automotive industry by reducing ergonomic impact for the drivers and improving it further through the flexibility to switch between modes.

Through increasingly efficient mass-production techniques, car-ownership has been made affordable to a large segment of the world's population, beginning in Europe and North America in the first decades of this century and recently extending rapidly throughout all other continents. The industry, however, is running out of major new opportunities for growth, and automotive markets in the Western World have entered the phase of maturity; this is typified by slowing growth and intensifying competition. These factors are driving fundamental change in the economics of the industry, and are forcing rationalisation and consolidation across the world. In a drive to remain competitive, the major Vehicle Manufacturers are relying more and more on the capabilities of their first-tier suppliers, and are pushing design and development responsibility further down the supply chain; suppliers are taking on a new role within the automotive industry and are increasingly becoming involved in the design and development of new products in collaboration with their major customers. The core theme throughout this research enquiry has been to investigate such practices (which have been termed co development), with particular emphasis placed on the European automotive industry. The literature within the areas of customer-supplier relationships and product development is wide and varying, and both bodies of knowledge are beginning to stress the importance of co-development in a number of industries. However, even though academics and industrialists are suggesting co development is necessary in today's marketplace, research into this area remains scarce and few insights into the improvement of such relationships can be found. This research has begun to close this gap by identifying those factors that can influence the successful transformation of co development. Through a series of focus groups, fifty-two concepts were identified that were seen to influence the success of co-development improvement activity - due to the nature of the focus group methodology, these concepts were wide-ranging and covered all aspects of the cross-company relationship, highlighting many -areas for further investigation. These concepts were reviewed and grouped, and four concepts plus sixteen sub-concepts chosen for additional analysis - these include a preparation phase, in which both organisations recognise the need for improvement and commit to enhance their existing relationship, the nature of communication across organisational boundaries, the alignment of working practices at all levels of the business, and an implementation phase in which actual improvements are realised and further sustained. These have been represented in an initial conceptual model that simply depicts the interdependencies that exist between the four high-level concepts. This conceptual model has been further tested and expanded through seven case studies; six cases were conducted at first-tier suppliers, whilst one was completed within a European-based VM. The major data collection tool used during these studies was the semi-structured interview, providing deep insights into co-development improvement from both sides of the relationship. The case studies only reiterated the importance of the concepts and sub-concepts within a co-development environment, and provided insights into the 'who, what, where, when, and how' of the topics under consideration. Finally. the concepts have been validated through a twelve-month action-research study, involving the actual implementation of the conceptual model in an industrial setting. The researcher gained first hand experience of co-development improvement, and observed an organisation struggling with the complexities of the cross-company environment. The knowledge gained throughout this period has not only emphasised the importance of the concepts and sub-concepts to co-development improvement, but has provided future implementers with insights into how one organisation has successfully transformed forty of their co-development relationships.

Thesis (M.B.A.)--Boston University. Missing page 8 in numbering only

Recently complex geometry and detailed Finite Element (FE) models have been used to capture the true behaviour of the structures for crashworthiness. Such model complexity, detailed FE model, high non-linearity of crash cases and high number of design variables for crashworthiness optimisation add to the required computational effort. Hence, engineering optimisation problems are currently highly restricted in exploring the entire design space and including the desired number of design parameters. Hence it is advantageous to reduce the computational effort to fully explore the design alternatives and also to study even more complex and computationally expensive problems. This thesis presents an efficient robust shape optimisation approach via the use of physical surrogate models, i.e. sub-models and models derived for the Equivalent Static Loads Method (ESLM). The classical simultaneous robust design optimisation (RDO) approach (where robustness analysis of each design is assessed) is modified to make use of the physical surrogate models. In the proposed RDO approach, design optimisations are made using sub-models and robustness analyses are made using either non-linear dynamic analysis or ESLM. The general idea is to approximate the robustness of designs at the start of the optimisation (using ESLM) and use accurate robustness evaluations (via non-linear dynamic analysis) towards the end of the optimisation where the optimisation has already found interesting regions of the design space. The approach is validated on crashworthiness design cases.

Estágio realizado na Bosch Car Multimedia Portugal, Ld.ª e orientado pelo Eng.º Miguel Viana / Tese de mestrado integrado. Engenharia Industrial e Gestão. Faculdade de Engenharia. Universidade do Porto. 2009

The conventional information used to guide automobile drivers in selecting their driving routes is the shortest-distance path (SDP). As several researchers have pointed out, driver route selection is a multiple criteria decision process. This research proposes a multiobjective path optimisation (MOPO) decision model to make a more precise simulation of the decision-making behaviour of driver route selection. Seven single-objective path optimisation (SOPO) decision models are taken into account to establish the MOPO decision model. They relate to travel time, travel cost, cumulative distance, roadway capacity, roadway grade, passed intersections and number of turns. To solve the MOPO problem, a two-stage technique which incorporates shortest path (SP) algorithms and techniques for solving the multiobjective programming problem and a path genetic algorithm (PGA) are proposed. In addition, algorithms such as Dijkstra, A* and GA are reviewed and algorithms that are applicable for solving the MOPO problems are suggested. Furthermore, new algorithms for solving least-node path (LNP) problem, corresponding to the objective of passed intersections, as well as minimum-turn path (MTP) problem, corresponding to the objective of number of turns, are developed. To conduct the empirical study, a software tool - the multiobjective path optimisation analysis tool (MOPOAT) - was implemented. It contains tools for constructing a road network and its corresponding network topology, the environment of coding techniques for solving the MOPO problems and tools for the manipulation, statistics, analysis and display of experimental results. The purpose of implementing the MOPOAT software is to provide more efficient, convenient and user-friendly tools for solving MOPO and SOPO problems so that an empirical study of real road networks can be carried out more easily. To demonstrate the advantages of the proposed model in supporting more diverse information to drivers to assist in route selection, several experiments were conducted utilising three real road networks with different roadway types and numbers of nodes and links. Techniques and algorithms such as the two-stage approach, Dijkstra and the PGA for solving the MOPO problem, and the Dijkstra, LNP and MTP algorithms for solving the SOPO problems were applied. Finally, to deal with improvements in computational efficiency for identifying SPs in a large road network and for population initialisation of the PGA, the critical-section (CS) approach and the seed-path expansion (SPE) approach are proposed. To compare the run time between the conventional SP and CS algorithms as well as the PGA and the SPE algorithms, tools were implemented with commercial GIS, and experimental tests were conducted using road networks with a large amount of nodes and links and different roadway types. Through these theoretical and empirical studies, several useful contributions and conclusions were obtained. Some of the most significant findings are: 1. The experimental results demonstrate the advantages of integration with commercial GIS packages in supporting both spatial and attribute data displays. It can be safely said that, assisted by the MOPOAT software, it is easy for automobile drivers to obtain the optimal paths of the SDP, LNP, MTP and MOPO problems in seconds, despite these problems being highly complex and difficult to resolve manually. 2. According to the experimental results, the proposed LNP, MTP and MOPO decision models give automobile drivers richer information for choosing their driving routes in a more diverse way. 3. It is shown by the experimental results that the SDP and LNP mostly locate different paths in both radial-circumferential and grid-type road networks, and that the total passed intersections by the SDP are greater than passed by the LNP. Moreover, it is revealed that ambiguous turns might occur in both radial-circumferential and grid-type road networks. 4. It is found that the number of nodes of the SDP is in general greater than the number of nodes of the LNP and MTP irrespective of the type of road network. 5. A sensitivity analysis for weights shows that as the weighting value of the SDP objective incrementally increases by 0.1 units, the corresponding SDP??s objective value varies either low or high. The same results also occur for the LNP and MTP objectives. This verifies the fact that the weighting coefficients do not reflect proportionally the relative importance of the objectives. Moreover, the MTP objective has the higher sensitivity in comparison with the other two objectives. 6. Despite utilising Dijkstra or PGA algorithms for solving the MOPO problem, the LNP and MTP algorithms have to be employed to solve the non-commeasurable problem, whereby the standardisation objective value can be obtained. In addition, without any assisting information the PGA might fail to reach the best-compromise solution. 7. It is found that the total run time for solving the MOPO problem by applying the Dijkstra algorithm is much faster than by the PGA. However, if the run time excludes the time needed for population initialisation, the PGA is much faster than the Dijkstra algorithm. 8. Based on calculated bottlenecks, the proposed CS approach partitions a SP into many critical sections in advance, with the result that a long SP can be obtained by combining all SPs of all CSs. The experimental results show that the run time of the CS algorithm is much faster than Dijkstra??s algorithm. Moreover, the test result for the P-pointer indicates that if the total number of nodes of a SP grows the computational efficiency of the CS algorithm becomes significantly better than the Dijkstra algorithm, and that the CS approach has the best performance. 9. The experimental result for the E-pointer reveals that the computational efficiency of the CS algorithm will decrease gradually as the number of selected CSs increases. Therefore, the total percentage of selected CSs suggested by the experimental result is no more than 30 percent. 10. According to the experimental results, the performance order among SDP, LNP and MTP algorithms from fast to slow is SDP, MTP and LNP, and the LNP algorithm requires much more time than the other two algorithms. 11. As the total nodes of a path increase, most of the run time for SDP and LNP also increases. However, there are still some paths that violate the above rule. This result verifies that the run time needed for solving SDP and LNP is not only affected by the node numbers but also depends on the network topology. 12. Run time for solving the MOPO problem by applying the PGA is faster than applying the Dijkstra algorithm, if the run time of the former algorithm does not take into account the population initialisation time. Nevertheless, if the run time of the former algorithm does take into account the population initialisation time, the latter algorithm is much faster than the former algorithm. 13. In comparing the run time for population initialisation, the run time of the evolution process by applying the PGA is quite small, and the bottleneck of the run time for solving MOPO problem by applying the PGA is the population initialisation. 14. The population initialisation time is reduced significantly by applying the SPE algorithm, and increases at a very slow rate as the number of nodes of a path increases. As the total nodes of a path grow ever larger, the computing time is reduced more noticeably.