Modelling production cost with the effects of learning and forgetting

Defining a dynamic model for calculating production cost is a challenging goal that requires a good fitting ability with real data over time. A novel cost curve is proposed here with the aim of incorporating both the learning and the forgetting phenomenon during both the production phases and the reworking operations. A single-product cost model is thus obtained, and a procedure for fitting the curve with real data is also introduced. Finally, this proposal is validated on a benchmark dataset in terms of mean square error

Modelling Operative and Routine Learning Curves in Manoeuvres in Locks and in Transit in the Expanded Panama Canal

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Piloting in the Panama Canal is exceptional as, due to its importance, the functions of the captains of vessels are taken over by pilots. Hence, prior to inauguration of the expanded canal, a limited number of pilots experienced on the existing canal were certified for the transit of Neopanamax vessels by means of planned and innovative individual learning. After this organisational training through operative training, with the implementation of the expanded canal in June 2016, the routine training started. Hence the learning curve in the performance of these manoeuvres will represent the growing skill acquired by both the pilots and the organisation. Given that the learning effect is measurable, this paper has the dual objective of determining two curve models: the organisation operative learning curve model and the routine learning curve model for pilots performing transit manoeuvres in the expanded Panama Canal waterways and the Cocolí and Agua Clara locks. Manoeuvre times in locks and transit in the whole of the canal were followed up continuously in the first 42 months of operation.The research of Salvador Naya and Javier Tarrío has been supported by MINECO grant MTM2017-82724-R, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2020-14 and Centro de Investigación del Sistema universitario de Galicia ED431G 2019/01), all of them through the ERDF. This work has been funded in part by Project 1-FACINA of the International Maritime University of Panama (UMIP).Xunta de Galicia; ED431C-2020-14Xunta de Galicia; ED431G 2019/01Universidad Marítima Internacional de Panamá; Project 1-FACIN

Sustainable Construction Engineering and Management

This Book is a Printed Edition of the Special Issue which covers sustainability as an emerging requirement in the fields of construction management, project management and engineering. We invited authors to submit their theoretical or experimental research articles that address the challenges and opportunities for sustainable construction in all its facets, including technical topics and specific operational or procedural solutions, as well as strategic approaches aimed at the project, company or industry level. Central to developments are smart technologies and sophisticated decision-making mechanisms that augment sustainable outcomes. The Special Issue was received with great interest by the research community and attracted a high number of submissions. The selection process sought to balance the inclusion of a broad representative spread of topics against research quality, with editors and reviewers settling on thirty-three articles for publication. The Editors invite all participating researchers and those interested in sustainable construction engineering and management to read the summary of the Special Issue and of course to access the full-text articles provided in the Book for deeper analyses

Conceptual Building Information Modelling Framework for Whole‐house Refurbishment based on LCC and LCA

The UK government aims at achieving 80% CO2 emission reduction by 2050 which requires collective efforts across all the UK industry sectors. In particular, the housing sector has a large potential to contribute to achieving the aim because the housing sector alone accounts for 27% of the total UK CO2 emission, and furthermore, 87% of the housing which is responsible for current 27% CO2 emission will still stand in 2050. Therefore, it is essential to improve energy efficiency of existing housing stock built with low energy efficiency standard. In order for this, a whole‐house needs to be refurbished in a sustainable way by considering the life time financial and environmental impacts of a refurbished house. However, the current refurbishment process seems to be challenging to generate a financially and environmentally affordable refurbishment solution due to the highly fragmented nature of refurbishment practice and a lack of knowledge and skills about whole‐house refurbishment in the construction industry. In order to generate an affordable refurbishment solution, diverse information regarding costs and environmental impacts of refurbishment measures and materials should be collected and integrated in right sequences throughout the refurbishment project life cycle among key project stakeholders. Consequently, various researchers increasingly study a way of utilizing Building Information Modelling (BIM) to tackle current problems in the construction industry because BIM can support construction professionals to manage construction projects in a collaborative manner by integrating diverse information, and to determine the best refurbishment solution among various alternatives by calculating the life cycle costs and lifetime CO2 performance of a refurbishment solution. Despite the capability of BIM, the BIM adoption rate is low with 25% in the housing sector and it has been rarely studied about a way of using BIM for housing refurbishment projects. Therefore, this research aims to develop a BIM framework to formulate a financially and environmentally affordable whole‐house refurbishment solution based on the Life Cycle Costing (LCC) and Life Cycle Assessment (LCA) methods simultaneously. In order to achieve the aim, a BIM feasibility study was conducted as a pilot study to examine whether BIM is suitable for housing refurbishment, and a BIM framework was developed based on the grounded theory because there was no precedent research. After the development of a BIM framework, this framework was examined by a hypothetical case study using BIM input data collected from questionnaire survey regarding homeowners’ preferences for housing refurbishment. Finally, validation of the BIM framework was conducted among academics and professionals by providing the BIM framework and a formulated refurbishment solution based on the LCC and LCA studies through the framework. As a result, BIM was identified as suitable for housing refurbishment as a management tool, and it is timely for developing the BIM framework. The BIM framework with seven project stages was developed to formulate an affordable refurbishment solution. Through the case study, the Building Regulation is identified as the most affordable energy efficiency standard which renders the best LCC and LCA results when it is applied for whole‐house refurbishment solution. In addition, the Fabric Energy Efficiency Standard (FEES) is recommended when customers are willing to adopt high energy standard, and the maximum 60% of CO2 emissions can be reduced through whole‐house fabric refurbishment with the FEES. Furthermore, limitations and challenges to fully utilize BIM framework for housing refurbishment were revealed such as a lack of BIM objects with proper cost and environmental information, limited interoperability between different BIM software and limited information of LCC and LCA datasets in BIM system. Finally, the BIM framework was validated as suitable for housing refurbishment projects, and reviewers commented that the framework can be more practical if a specific BIM library for housing refurbishment with proper LCC and LCA datasets is developed. This research is expected to provide a systematic way of formulating a refurbishment solution using BIM, and to become a basis for further research on BIM for the housing sector to resolve the current limitations and challenges. Future research should enhance the BIM framework by developing more detailed process map and develop BIM objects with proper LCC and LCA Information

Chatbot de Suporte para Plataforma de Marketing Multicanal

E-goi is an organization which provides automated multichannel marketing possibilities. Given its system’s complexity, it requires a not so smooth learning curve, which means that sometimes costumers incur upon some difficulties which directs them towards appropriate Costumer Support resources. With an increase in the number of users, these Costumer Support requests are somewhat frequent and demand an increase in availability in Costumer Support channels which become inundated with simple, easily-resolvable requests. The organization idealized the possibility of automating significant portion of costumer generated tickets with the possibility of scaling to deal with other types of operations. This thesis aims to present a long-term solution to that request with the development of a chatbot system, fully integrated with the existing enterprise modules and data sources. In order to accomplish this, prototypes using several Chatbot management and Natural Language Processing frameworks were developed. Afterwards, their advantages and disadvantages were pondered, followed by the implementation of its accompanying system and testing of developed software and Natural Language Processing results. Although the developed overarching system achieved its designed functionalities, the master’s thesis could not offer a viable solution for the problem at hand given that the available data could not provide an intent mining model usable in a real-world context.A E-goi é uma organização que disponibiliza soluções de marketing digital automatizadas e multicanal. Dada a complexidade do seu Sistema, que requer uma curva de aprendizagem não muito suave, o que significa que os seus utilizadores por vezes têm dificuldades que os levam a recorrer aos canais de Apoio ao Cliente. Com um aumento de utilizadores, estes pedidos de Apoio ao Cliente tornam-se frequentes e requerem um aumento da disponibilidade nos canais apropriados que ficam inundados de pedidos simples e de fácil resolução. A organização idealizou a possibilidade de automatizar uma porção significativa de tais pedidos, podendo escalar para outro tipo de operações. Este trabalho de mestrado visa apresentar uma proposta de solução a longo prazo para este problema. Pretende-se o desenvolvimento de um sistema de chatbots, completamente integrado com o sistema existente da empresa e variadas fontes de dados. Para este efeito, foram desenvolvidos protótipos de várias frameworks para gestão de chatbots e de Natural Language Processing, ponderadas as suas vantagens e desvantagens, implementado o sistema englobante e realizados planos de testes ao software desenvolvido e aos resultados de Natural Language Processing. Apesar do sistema desenvolvido ter cumprido as funcionalidades pelas quais foi concebido, a tese de mestrado não foi capaz de obter uma solução viável para o problema dado que com os dados disponibilizados não foi possível produzir um modelo de deteção de intenções usável num contexto real

Managing the Potential of Modularization and Standardization of MEP Systems in Industrial Buildings - Guidelines for improvement based on lean principles

Modularization and standardization (M&S) of MEP (mechanical, electrical, and plumbing) systems improve end customer value according to lean concepts and principles. However, the imple-mentation of M&S is challenged. This research includes three main parts

Bayesian learning in performance. Is there any?

We propose and implement a Bayesian learning model for performance. The model implies a specific distribution for performance / technical inefficiency which we exploit in the context of stochastic frontier models. As the theoretical model is ambiguous with respect to what constitutes existing “experience”, we propose and implement alternative specifications. The estimation and inference techniques are based on Bayesian analysis using Markov Chain Monte Carlo methods. We apply the new techniques to a data set of large U.S. banks. Our findings indicate that there is some learning in technical inefficiency although there is limited evidence, if at all, that jumps in experience are related to productivity growth. However, this effect is distinctly pronounced for the 2007-2010 period but much less significant afterwards

A system dynamics model for the strategic analysis of options for sourcing engineering design

Thesis (S.M.)--Massachusetts Institute of Technology, System Design and Management Program, 2008.Includes bibliographical references (p. 128-131).EC (Engineering Change) is the natural by-product of the Engineering Design process. There are two types of EC: Revisions and Defects Correction. Revisions arise because Engineering Design is an iterative process, requiring Engineers to implement necessary Revisions to the design of a product or systems to improve performance measures. Defects on the other hand are pure design errors, and arise from the fact that the Engineering Design work is not being accomplished with Perfect Quality. These Defects must therefore be corrected in what is termed Rework. EC is the critical factor in determining Lead Time and Labor cost of an Engineering Design work. The generation of Rework - requiring EC depends on several factors including : Quality, Design Complexity, Time to Discover Rework, Time for Issues Resolution, Hiring New and less experienced staff and Over Time work. This thesis presents a Systems Dynamics Model which incorporates these factors as exogenous variables to enable the simulation of their impacts on endogenous variables such as Lead Time and Labor costs. Since these factors exhibit wide variability when the Engineering Design is accomplished In-House compared to when it is Outsourced, the model is therefore a tool that can help an OEM in the Strategic Analysis of Options for the Sourcing of Engineering Design work. A simulation example is given in which an Engineering Design with 474 Initial Designs required 400 fully experienced Engineers to accomplish in 360 Days and a quality level of 52% (the Baseline case). The OEM had only 200 fully experienced Engineers on hand. Facing a staff capacity constraint, this OEM therefore explores a number of In-House Sourcing Options (Hiring and Over Time) and a number of Outsourcing Options (Suppliers with staff capacities of 400 to 1,000, and low (40%) and high (60%) Quality levels.(cont.) The analysis concludes that there are three factors that have major impacts on the viability of Outsourcing. First, when the volume of work to be accomplished is high, Outsourcing of engineering design is a viable option. However, as the complexity of the design increases, outsourcing of engineering design becomes increasingly less attractive. Finally, the analysis found that supplier quality is critical to successful outsourcing. Outsourcing to regions with low labor rates is attractive for labor cost reduction, but do not solve the problem of poor supplier quality with negative impact on Lead Time.by Charles Mmaduka Ufongene.S.M

Evaluating manufacturing flexibility driven by learning

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Page 126 blank. Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 110-115).A defining feature of modern industry is operating in a context of nearly continuous technological change. Nevertheless, industrial decision-makers must select technologies and implement production strategies even in the face of known-to-be-incomplete information and environmental uncertainties. Further complicating the picture, the performance, including the economic performance, associated with novel technology options is likely to change over time. To address this problem, two approaches are possible: improving the quality of currently available information, and implementing flexible production strategies. The present work characterizes how the former approach impacts the valuation of the latter. First, a dynamic approach integrating learning curves and process-based cost modeling is used to examine learning in manufacturing, thus allowing decision-makers to incorporate information about expected technology evolution into their economic evaluations of technology. The approach is applied to an automotive assembly process, and quantifies the cost impacts of learning improvements in manufacturing time, downtime, and defect rates. Analysis can be used to focus learning activities on primary learning operational drivers, and to forecast cost improvements for a novel process. Flexibility strategies are often focused on capital-intensive processes, while labor-intensive processes are thought to be inherently flexible. The existence of learning effects, however, implies that labor flexibility has costs and, potentially, benefits in the context of uncertainty. A simple automotive assembly case is used here to illustrate the impact of manufacturing learning on labor flexibility and its economic value. A framework using cash-flow and decision tree models is introduced to quantify the costs and benefits of acquiring worker flexibility, and improve information available for strategic decision-making in labor-intensive systems. The front-end characterization of the technical drivers of learning provides insight into how the value of flexibility can be impacted at the operational level, enabling managers to prioritize improvements and minimize the costs of flexibility.by Marie-Claude Nadeau.S.M.in Technology and Polic