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One of the main problems brought by large-scale 3D printers is the lack of standardization of machines and the potential of low-quality products. If a company invests in an inexpensive 3D printer then the risk of a bad quality product increases. On the other hand, a high-end Large-scale 3D printer would cost millions of dollars to produce a trustworthy result. Regardless, the traditional manufacturing route will always be preferred by production companies. Many different 3D printers produce very different products, making there a lack of universal standards in 3D printing technologies. Therefore, manufacturers compare their products with other manufacturers' methods worrying that they would vary in terms of quality, strength, and reliability. This causes a continuous wariness in the 3D printing technology, making companies always judge the risks compared to the benefits.
Variational Model Reduction for Non-hydrostatic Stratified Flows in the Mid-latitude and the Equator
(2022)
This thesis studies balance models for a rotating stratified three-dimensional fluid on a tangent plane with full Coriolis force. Derivations are done for two different regions, namely mid-latitude and equator, which we considered separately. Each model is studied via a variational approach which is based on Lagrangian dynamics assuming smallness of the Rossby number and allowing for anisotropy in the horizontal length scales. We assume semigeostrophic scaling, akin to the derivation of the L 1 model by Salmon (1985) for the rotating shallow water equations. Contrary to Salmon’s derivation, we start with an arbitrary change of coordinates and then choose the transformation to fix the degeneracy on the first order of the Lagrangian, L 1, as suggested by Oliver (2006). In our setting, the full projection of the rotation vector of the Earth is considered, so that the horizontal component of the Coriolis vector is taken into account. For each model, conservation laws for the energy and the potential vorticity are valid because of the Hamiltonian structure. Our first model on f-plane is the most general model obtained so far in semi-geostrophic scaling. The other model concerns balance model on the equatorial β-plane. Under the additional assumption of construction of zero-meridional velocity as suggested by the leading order dynamics, an equatorial balance model is obtained.
Optimal balance is a numerical decomposition method of geophysical flows into a balanced and unbalanced components without any asymptotic analysis. It was introduced under optimal potential vorticity (PV) balance by Viúdez and Dritschel (2004) in a special semi-Lagrangian PV-based scheme. The method adiabatically deforms the nonlinear model into its linear form where mode decomposition is exact. It leads to a boundary value problem in time where gravity waves are removed at the linear end and a base-point coordinate is restored at the nonlinear end. This problem is solved by an iterative backward-forward nudging scheme. As global geophysical ocean models use primitive variables, we study optimal balance on an existing f-plane shallow water model in the primitive velocity-height variables. Our model, nevertheless, includes kinematic PV-inversion formulas if the PV is base point.
We, here, systematically investigate our numerical model for several design parameters. We found that optimal balance works with PV-based projectors which are the most robust choice with primitive variable-based projectors which are useful for general domains and global models. The PV-based projectors are the linear oblique projector and the base point PV. The linear oblique projector can be reformulated as a PDE-based projector preserving linear PV. Besides, the height field as a prominent candidate of base point and a linear PDE-based projector support more general cases.
The method returns high-quality balance with rapid convergence of the nudging scheme, but its convergence is, still, an open question. We proved the ''quasi-converge'' of the nudging iterates up to a small termination residual, and this residual is as small as the balance error which is of algebraic order in the time-separation parameter for a lower-dimensional system. Hence, optimal balance is an accurate diagnostic tool in primitive variables and can be implemented on complicated models without fundamental obstacles.
The focus of the study is to conduct a comparative analysis of the most widely adopted methods of safety stock calculation. Firstly, it aims to identify the most widely adopted methods of safety stock calculation and investigate their strengths and weaknesses. Secondly, the thesis aims to analyse the demand patterns that operations managers often encounter and their behaviours. The safety stock calculations will then be compared to one another by running a simulation with different demand patterns using each of them. Finally, recommendations will be made on which demand patterns, if any, each of these methods is best applied to.
The overreaching aim of this paper is to introduce a strategy for lean methods implementation in production systems. The first sub-objective is to describe the lean manufacturing philosophy and discuss research findings on the topic of lean methods and their impact on production system performance. The second sub-objective is to develop a system dynamics model based on the findings obtained through literature review. The third sub-objective is to analyze the results and derive recommendations for lean methods implementation that will ensure long term continuous performance improvement.
This work aims to analyze and cluster demand forecasting methods and approaches in previous research endeavors which have been recently going through an obvious trend and direction towards a more digital supply chain and automated forecasting methods. For this, developments in the fashion industry are addressed and previous forecasting methods are linked to current market features. Current existing challenges and barriers are identified in order to be able to propose future research areas and framework in demand forecasting in the Fast Fashion Industry.
This Research paper focuses on identifying & countering the Challenges of Industry 4.0. Although Industry 4.0 has been a boom of the century, the underlying challenges still need to evaluated and counter measure must be taken in order to have long-term goals satisfied. Therefore, first part of the research focuses on identifying the key challenges and then second part of the research has been dedicated to counter measure. The research contains serious of interview ranging from Industry 4.0 experts to end user of these technologies to validate the identified challenges and counter measure. Thus, the research has a practically backed evidence and real time problem scenarios have been well documented through the course of research. Therefore, this research points out six quantified and qualified Industry 4.0 challenge cluster. They are 1. Economic Challenges, 2. Technical Challenges, 3. Competency Challenges, 4. Cultural Challenges, 5. Managerial Challenges 6. Collaborative challenges. Thus, the identified counter measure falls into four areas of system of Innovation. They are 1. Role of Central Government 2. Co-operation of State Universities and Industries 3. Role of State Government in Promoting Technology Fairs 4. Role of Company Management and Unions. This research also a Supply Chain Limitation which must be considered. Therefore, the research serves as a base guideline for companies in knowing the challenges and provides a direction for the mitigating these challenges through System of Innovation.
Industry 4.0 is a current trend of digital transformation and integration of processes into the digital environment using automation, big data, and Internet of Things (IoT). The divergence of the world economy, contrary to the convergence infers the increasing gap between developing and developed countries. Although it is true that there are significant productivity and efficiency gains with the upcoming fourth industrial revolution, it is also essential to examine the differences in the impact of automation on these two economies. The thesis is an attempt to investigate how unanticipatedly Industry 4.0 and the upcoming era of automation supports the divergence of the world economy, contributing to the gap between the developed (Japan, USA, Germany) and developing countries (India, Nigeria, Mexico).
The higher the population, the higher the number of people contributing to economy, has been the centre argument for convergence. But how different is the economic impact, when it is the industrial robots working for the economy and when the country even with low population can achieve equally high output? The paper dives over these topics with 1) comparative analysis where an outlook of Industry 4.0 is observed by examining previous three industrial revolutions 2) macroeconomic analysis, where population demographics, labour redeployment and marginal cost-benefit of Industry 4.0 are inferred to discuss divergence of economies. The transdisciplinary paper uses concepts from economics and business disciplines and concludes with policies for developed and developing countries to prepare for the upcoming transition.
Global manufacturing networks and the underlying global supply chains form the centerpiece of automotive production. Over the last decades, original equipment manufacturers established overseas plants in the course of their expansion strategy and employed so-called knocked-down supply chains to ship all parts pre-assembled and arranged in kits to them. The overseas plants have matured into fully-equipped plants by taking over value-adding processes. As a consequence, the global manufacturing networks have shifted their focus away from simplification toward performance. The underlying knocked-down supply chains, however, have not adapted and still feature high inventories, lead times and costs.
Even though knocked-down supply chains play a key role in global manufacturing networks, they have not been integrated. It is not possible to evaluate their fit and to derive the requirements. Despite the intense effort to improve the performance in the factories, there is little research on improvement levers in the context of knocked-down supply chains.
This Thesis intends to explore how knocked-down supply chains can be aligned with global manufacturing networks. It conducts a cross-case study to provide an overview of current knocked-down supply chains and global manufacturing networks. The Thesis develops an integrated framework that matches knocked-down supply chains and global manufacturing networks and identifies weak spots in supply chain performance. The Thesis then applies a two-fold approach. It explores the general working principle of knocked-down supply chains by means of intermodal transportation. Gaining impetus from lean management, the Thesis then identifies improvement levers and subsequently evaluates their effect on knocked-down supply chains. The Thesis shows that the supply chain performance of knocked-down supply chains and thus the fit with the global manufacturing network can be improved.
Commonly, methods applied in production planning may lead to production orders flowing
across similar sequences of machines within similar periods of time. However, within such
spatiotemporal neighbourhoods, interdependency effects among production orders may arise,
causing compounding delays. The importance of anticipating interdependencies amongst
production orders during production planning is key to accurately predict logistics performance such as lead time or expected delays. This is a challenging task for production planners, as interdependencies arise during operations, are difficult to foresee, and can be caused by a multitude of different factors. Only little research has been carried out to establish a generic and measurable understanding of the root-causes of interdependencies in manufacturing systems. In other research areas, such interdependency effects are explored as a key impact factor on system performance. Particularly in physics, research on granular matter systems has led to the development of multiple theories and concepts of particle-particle interactions, summarised here as Granular Matter Theory (GMT). In this thesis, we draw on these concepts in order to define and measure interdependency effects for manufacturing systems and discover a negative relation between to logistics performance indicators. Furthermore, we provide first evidence on some structural and non-structural impact factors that drive such effects and derive recommendations for practitioners in production planning.
