Job profiling: How artificial intelligence supports the management of complexity induced by product variety

Firms and supply chains (SC) increasingly are forced to customise products and optimise processes since today’s markets are, on average, more demanding in terms of both costs and customer satisfaction. Generally, when product variety (PV) increases not only improves sales performance, since products offered better fit customers’ expectations, but also increases the complexity in SC processes management, rising operational costs. For that reason, accurate management of product diversity is a fundamental point for the brands' success, which is why it is going to be investigated in that project. Moreover, firms’ managers apply strategies to mitigate or accommodate this complexity, avoiding the customer satisfaction and cost trade-off to remain competitive and survive. However, we were wondering if it is enough. Artificial Intelligence (AI) has emerged to stay. Digitalisation era, data availability, and the improvement in computing power have boomed AI’s potential in improving systems, controlling processes, and tackling complexity. These strengths are suitable to help managers not only to tackle the complexity arising from PV but also to boost the supply chain performance (SCP

City strategy : final evaluation

The City Strategy (CS) concept was first announced in the 2006 Welfare Reform Green Paper – A new deal for welfare: Empowering people to work. CS was designed at a time of growth in the national economy to combat enduring pockets of entrenched worklessness and poverty in urban areas by empowering local institutions to come together in partnerships to develop locally sensitive solutions. It was premised on the idea that developing a better understanding of the local welfare to work arena would allow partnerships to align and pool funding and resources to reduce duplication of services and fill gaps in provision. The ‘theory of change’ underlying CS suggested that such an approach would result in more coordinated services which would be able to generate extra positive outcomes in terms of getting people into jobs and sustaining them in employment over and above existing provision. CS was initially set to run for two years from April 2007 to March 2009 in 15 CS Pathfinder (CSP) areas, varying in size from five wards in one town through single local authority areas to subregional groupings of multiple local authority areas, across Great Britain. In July 2008, the Secretary of State for Work and Pensions announced an extension for a further two years to March 2011. In April 2009, two local areas in Wales, which were in receipt of monies from the Deprived Areas Fund (DAF), were invited by the Department for Work and Pensions (DWP) to form local partnerships with a similar remit to the CSPs, albeit more limited in scope – to develop locally sensitive solutions to economic inactivity, to the CSPs. During the period that the CS initiative was operational, economic conditions changed markedly with a severe recession, followed by fragile recovery. The CSPs had to cope with ongoing changes in policy throughout the lifetime of the CS initiative, including a General Election and a new Coalition Government at Westminster early in the fourth year. While policy changes are a fact of life for local practitioners operating in the welfare to work arena, the global recession in 2008/09 marked a fundamental change in the context in which local partnerships operated

EVALUATION OF SETUP ECONOMIES IN CELLULAR MANUFACTURING

This dissertation addresses two research questions relating to the role of setups in discrete parts manufacturing. The first research topic uses a carefully designed simulation study to investigate the role of setup economies in the factory-wide conversion of functional layouts (job shops) to cellular manufacturing. The model-based literature shows a wide dispersion in the relative performance of cellular manufacturing systems as compared to the original job-shop configurations, even when the key performance measure is flow time and the assessment tool used is simulation. Using a standardized framework for comparison, we show how this dispersion can be reduced and consistent results can be obtained as to when the conversion of the job shop is advantageous. The proposed framework standardizes the parameters and operational rules to permit meaningful comparison across different manufacturing environments, while retaining differences in part mix and demand characteristics. We apply this framework to a test bed of six problems extracted from the literature and use the results to assess the effect of two key factors: setup reduction and the overall shop load (demand placed on the available capacity). We also show that the use of transfer batches constitutes an independent improvement lever for reducing flow time across all data sets. Finally, we utilize the same simulation study framework to investigate the benefits of partial transformation, where only a portion of the job shop is converted to cells to work alongside a remainder shop. The second research question examines the role of dispatching rules in the reduction of setups. We use queueing models to investigate the extent of setup reduction analytically. We single out the Alternating Priority (AP) rule since it is designed to minimize the incidence of setups for a two-class system. We investigate the extent of setup reductions by comparing AP with the First-Come-First-Served (FCFS) rule. New results are obtained analytically for the case of zero setup times and extended to the case of non-zero setup time through computational studies

A structured method for the optimization of the existing last mile logistic flows

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceIn a fast-moving world some business exists due to the interconnectivity between countries. This happens because transports are able to reach the other side of the globe within few days and without being too expensive compensating the lower costs of production and competitive advantages. This is true for well-organized and big supply chains but even them can benefit from integration with disconnected and more complex supply chain as it is the case of e-commerce chains. The transaction of small packages from online shopping required in a totally distinct country of the place of production have very specific characteristics as they are spot flows, hard to predict and to combine with other goods owing to the fact that the destination of flows are different every time and it is not always worth it to dedicate a transport for such a small goods value and in addition most times, logistics have to answer to some challenging marketing requirements meaning they have time windows to fulfil. Last mile is a big part of logistics transports and is one important part of it that can really help companies having better prices and revenues for their transports. Last mile solutions need to be easy to implement and really have to translate in quick gains to logistic companies that are largely reducing their margins to increase competitiveness. In this context, the study aims to investigate and define a method following design Research Methodology hopping to draw some innovative solutions for the problem of last mile. In this respect, the work developed intends to study the solutions already implemented and extract insights on how distribution is made and how to maximize last mile profit through the mature of an algorithm able to reduce inefficiencies in a simple way without having to wiggle too much the structure of businesses as resources of last mile service providers are understood to be scarce as many last mile companies are small sized and running under big logistic players. The solution aims to attain the different marketing requirements exactly as it was defined without having to compromise anything but still being able to make good profit margins and perhaps make room for new opportunities to arise that previously were not profitable

Horizontal Cooperation in Transport and Logistics.

This thesis deals with horizontal cooperation in transport and logistics. It contains a comprehensive discussion of the available academic literature on this topic, many practical examples, and an empirical investigation of opportunities and impediments. Furthermore, three enabling concepts for horizontal cooperation in transport and logistics are developed. The analysis is practice oriented in the sense that most of the results are based on real-life datasets. In case studies conducted, the most important goal is to learn lessons that are also applicable to other cases or industries. By contrast, in chapters that have a more theoretical point of departure, efforts are made to draw conclusions that are directly applicable in practice. Many different research techniques are used in this thesis. They include case study analysis, surveys, exploratory factor analysis, regression, game theory, vehicle routing heuristics, and facility location heuristics.

The application of social marketing in promoting sustainable transportation

The traditional approach of dealing with transportation issues appears to be insufficient in bringing about sustainable urban traffic, as it does not take into account complex psychological processes assisting people in making their travel choices. New approaches are required to raise the effectiveness of transportation policies, by facilitating higher levels of public acceptance and engagement in promoted activities. The current thesis aims to assist policy-makers and program-designers in making transportation systems more sustainable by employing a social marketing approach. It provides an in-depth understanding of what social marketing is, demonstrates its advantages over the traditional transportation planning process, and explores its successful application in Lund and Malmo, located in the south of Sweden – two of the leading European cities in sustainable transportation systems