A methodology for the selection of new technologies in the aviation industry

The purpose of this report is to present a technology selection methodology to quantify both tangible and intangible benefits of certain technology alternatives within a fuzzy environment. Specifically, it describes an application of the theory of fuzzy sets to hierarchical structural analysis and economic evaluations for utilisation in the industry. The report proposes a complete methodology to accurately select new technologies. A computer based prototype model has been developed to handle the more complex fuzzy calculations. Decision-makers are only required to express their opinions on comparative importance of various factors in linguistic terms rather than exact numerical values. These linguistic variable scales, such as ‘very high’, ‘high’, ‘medium’, ‘low’ and ‘very low’, are then converted into fuzzy numbers, since it becomes more meaningful to quantify a subjective measurement into a range rather than in an exact value. By aggregating the hierarchy, the preferential weight of each alternative technology is found, which is called fuzzy appropriate index. The fuzzy appropriate indices of different technologies are then ranked and preferential ranking orders of technologies are found. From the economic evaluation perspective, a fuzzy cash flow analysis is employed. This deals quantitatively with imprecision or uncertainties, as the cash flows are modelled as triangular fuzzy numbers which represent ‘the most likely possible value’, ‘the most pessimistic value’ and ‘the most optimistic value’. By using this methodology, the ambiguities involved in the assessment data can be effectively represented and processed to assure a more convincing and effective decision- making process when selecting new technologies in which to invest. The prototype model was validated with a case study within the aviation industry that ensured it was properly configured to meet the

Lean technology development

Thesis (S.M.)--Massachusetts Institute of Technology, Technology and Policy Program, 2001.Includes bibliographical references (leaves 89-91).In today's corporate world, successful technology management is separating market leaders from laggards. Because technology is in constant change and what is state-of-the-art today will be obsolete tomorrow, it is not companies with the best technologies that ultimately succeed. Instead, successful companies are those that succeed in institutionalizing and sustaining an efficient technology development process. Moreover, this process must be continuously improved by applying new techniques and concepts to cope with the increasing challenges of technology management. This thesis will explore the extent to which Lean principles can be applied in technology development and how they can contribute to achieving new technology development imperatives (fast cycle time, increasing number of technology introductions, etc.). In order to answer these questions, the thesis proceeds in a logical manner by decomposing the objectives of technology development into organizational solutions using Axiomatic Design. Then, Lean principles as they have developed within the Product Development Focus Team of the Lean Aerospace Initiative are mapped into the above decomposition. The research concludes that under some additional considerations, Lean principles do lead to the achievement of technology development objectives. More, the above theoretical research is applied to a real world case: Technology development at Ford Motor Company. After an assessment of the current process, opportunities of improvement are identified and a leaner process is proposed. Finally, issues and opportunities with OEMs-Suppliers partnerships for new technological systems development are studied. The objective was to formulate policies and make recommendations for a better management of technology supply.by Salim Bouzekouk.S.M

A Strategic Roadmap for the Manufacturing Industry to Implement Industry 4.0

Industry 4.0 (also referred to as digitization of manufacturing) is characterized by cyber physical systems, automation, and data exchange. It is no longer a future trend and is being employed worldwide by manufacturing organizations, to gain benefits of improved performance, reduced inefficiencies, and lower costs, while improving flexibility. However, the implementation of Industry 4.0 enabling technologies is a difficult task and becomes even more challenging without any standardized approach. The barriers include, but are not limited to, lack of knowledge, inability to realistically quantify the return on investment, and lack of a skilled workforce. This study presents a systematic and content-centric literature review of Industry 4.0 enabling technologies, to highlight their impact on the manufacturing industry. It also provides a strategic roadmap for the implementation of Industry 4.0, based on lean six sigma approaches. The basis of the roadmap is the design for six sigma approach for the development of a new process chain, followed by a continuous improvement plan. The reason for choosing lean six sigma is to provide manufacturers with a sense of familiarity, as they have been employing these principles for removing waste and reducing variability. Major reasons for the rejection of Industry 4.0 implementation methodologies by manufactures are fear of the unknown and resistance to change, whereas the use of lean six sigma can mitigate them. The strategic roadmap presented in this paper can offer a holistic view of phases that manufacturers should undertake and the challenges they might face in their journey toward Industry 4.0 transition

Lean Aerospace Initiative (LAI) MIT Research Studies Applicable to Systems Engineering

This publication contains abstracts for past research thesis projects related to systems engineering completed within the LAI research group at Massachusetts Institute of Technology

COMPARATIVE CASE STUDY: EXPEDITIONARY FIGHTING VEHICLE AND AMPHIBIOUS COMBAT VEHICLE

The Marine Corps Expeditionary Fighting Vehicle (EFV) program cost taxpayers over $3 billion from inception to cancellation. The Amphibious Combat Vehicle (ACV) attempts to replace the Amphibious Assault Vehicle (AAV) and pick up where the EFV left off. A program comparison can be used to learn from previous management mistakes and prevent failures of this magnitude. By analyzing the two amphibious vehicle programs, I assess pertinent successes and failures against the model with available program management tools, including decision science principles. This report compares key junctures in both programs' life cycles and offers recommendations for future amphibious combat vehicle acquisition. The conclusion reveals that unbalanced cost and schedule increases overpowered the EFV performance goal, leading to cancellation. As a result, the ACV shows less performance but at a lower cost in comparison. Through research, acquisition professionals can better understand the importance of oversight, find solutions, and effectively equip themselves to manage major defense weapon systems.ARPMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

Engineering learning of sustainable product lifecycle through CDIO

Sustainable development is an optional CDIO (Conceive, Design, Implement, Operate) standard in the engineering curriculum, however, due to the impact of climate change on society and the environment, sustainability is now seen as a crucial aspect of learning. Engineering has contributed to climate change through non-sustainable solutions, so it is important to implement a sustainable CDIO standard in the engineering curriculum. In the UK, the Engineering Council already requires engineering-accredited courses to embed sustainability into the engineering curriculum, learning, practice and assessment following the UNESCO sustainability goals. This means that the engineering curriculum is required to provide learning opportunities for students to engineer sustainable solutions that are fit for all of society. This paper illustrates how the optional CDIO standard: sustainable development has been implemented in a second-year capstone project module The module challenges students to research and develop a low-carbon footprint product for World Rugby The module placed learning emphasis on a diamond TQM+ paradigm (Time, Quality, Management, Sustainability, Health & Safety) and challenged students to consider environmental impact and circular economy solutions. The paper reports on student learning, challenges, and successes in satisfying this diamond TQM+ paradigm to engineer sustainable rugby equipment (products, clothing, footwear, PPE) solutions and opportunities for further student learning development

Designing an AI-enabled Bundling Generator in an Automotive Case Study

Procurement and marketing are the main boundary-spanning functions of an organization. Some studies highlight that procurement is less likely to benefit from artificial intelligence emphasizing its potential in other functions, i.e., in marketing. A case study in the automotive industry of the bundling problem utilizing the design science approach is conducted from the perspective of the buying organization contributing to theory and practice. We rely on information processing theory to create a practical tool that is augmenting the skills of expert buyers through a recommendation engine to make better decisions in a novel way to further save costs. Thereby, we are adding to the literature on spend analysis that has mainly been looking backward using historical data of purchasing orders and invoices to infer saving potentials in the future – our study supplements this approach with forward-looking planning data with inherent challenges of precision and information-richness

A stochastic approach for product costing in manufacturing processes

Nowadays, manufacturing companies are characterized by complex systems with multiple products being manufactured in multiple assembly lines. In such situations, traditional costing systems based on deterministic cost models cannot be used. This paper focuses on developing a stochastic approach to costing systems that considers the variability in the process cycle time of the different workstations in the assembly line. This approach provides a range of values for the product costs, allowing for a better perception of the risk associated to these costs instead of providing a single value of the cost. The confidence interval for the mean and the use of quartiles one and three as lower and upper estimates are proposed to include variability and risk in costing systems. The analysis of outliers and some statistical tests are included in the proposed approach, which was applied in a tier 1 company in the automotive industry. The probability distribution of the possible range of values for the bottleneck’s cycle time showcase all the possible values of product cost considering the process variability and uncertainty. A stochastic cost model allows a better analysis of the margins and optimization opportunities as well as investment appraisal and quotation activities.This work is supported by: European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020) [Project nº 39479; Funding Reference: POCI-01-0247-FEDER-39479]

Managing the costs of new product development projects: a longitudinal case study at an automotive company

The overarching research topic of this dissertation is the management of the costs of new product development projects. New product development (hereinafter NPD) is essential for most companies, as the introduction of innovative products is crucial for their long-term success. Due to the high level of uncertainty that comes with the innovative process of product development, the management of NPD costs is a highly challenging task. We illuminate the field of NPD cost management from two perspectives, which represent our research topics. The first research topic of this thesis is the estimation of NPD costs. NPD costs are costs triggered by the activities that companies pursue to technically develop new products (i.e., labor costs of engineers, project managers, designers, and quality assessors, costs for tools and software required in NPD, costs of material and components required for testing and prototyping, and NPD-related overhead costs). Many authors have presented methods for product cost estimation in general, mostly focusing on overall product costs or direct material costs. Limited research is available about the estimation of the specific cost type of NPD costs. We conduct three studies to contribute to this gap. First, we give an overview of the status quo regarding NPD cost estimation. We do this by conducting a systematic literature review on methods for this purpose. Second, we develop and present the NPD cost benchmarking method. With this method, which is mostly built on external data, we add a new approach to the literature on NPD cost estimation methods. As third study in the context of NPD cost estimation, we present a case study in which we provide detailed, empirical insights on the challenges in NPD cost estimation, and on the application of the NPD cost benchmarking method in particular. The second research topic of this thesis concerns decision-making processes during NPD projects. In this uncertain and dynamic environment, decision-makers often rely on heuristics to choose between alternative options for responding to unpredicted developments during NPD projects (for example, changes in market demands, technical challenges, or new information about competitors). Empirical insights are mostly missing about how such decisions are made. Our fourth study provides insights on the use of heuristics in ongoing NPD project managerial decision-making by conceptualizing and empirically testing the within-project NPD cost compensation heuristic. This dissertation was supervised by Prof. Dr. Marc Wouters from KIT’s chair of Management Accounting at the Institute of Management. It is written in English language and the author aims to obtain the title of Dr. rer. pol

A Process Model for ERP Upgrade and Replacement Decisions

Background: This paper aims to develop an effective decision making (DM) process for ERP change or replacement. ERP in most organizations constitutes a key critical system of high complexity with many stakeholders. A major change activity for such a system therefore exposes an organization to great risks, and thus should be well organized. Method: A design science approach was chosen for this research. Based on a review of related literature and evidence of the DM process at different companies, a general process of DM for ERP upgrade was designed, and later evaluated and improved through a case study approach. Results: The decision process assumes a model with variables describing characteristics and performance of possible alternatives, and the decision is decomposed into steps with three loops that are executed iteratively. We believe that the findings and approach can be useful both for the immediate problem context and also for other IT-related DM problems. Conclusions: The main outcome is the new process of DM that includes several novel contributions: three main loops of DM, multiple repetition of loops, and possible returns to the starting point