Context-Aware Mass Customization Construction System - Methods for user captured as-built plans

In the closing chapter of this book we would like to share with our readers our view about the future of the customer centric enterprise and the enabling strategies of mass customization, customer integration, and personalization. We will also comment on fields for further research necessary for the development of new processes, tools and programs for integrating the customer into value creating activities, both on the technological and the operational process side. We identify six areas where - from our perspective and within our field of knowledge - more research is needed most. These are also fields which we think require special attention when implementing a mass customization system: (1) Issues concerning the design of products and product architectures. (2) Consumer behavior with customer interaction tools. (3) Drivers of customer satisfaction and dissatisfaction with custom made products. (4) Impact of integrating a user and customer into value creation on knowledge management and information management. (5) Capability analysis and systems engineering for concurrency in value chains. (6) Measurement of value contribution in mass customization systems.

Since the last decades, companies have been increasing product variety, thus forcing manufacturers to create more and more customized products. To manage such contexts, manufacturing companies are adopting mass customization, i.e., a manufacturing strategy that aims to offer customized goods at low cost. Recently, advancements in information system technologies provide new opportunities for the manufacturing sector. In particular, the concept of Industry 4.0, i.e., the application of the concepts of smartness and networking to the manufacturing environment, is providing tools to reduce the complexity of managing production systems. Despite the relevance of both areas, how mass customization can be integrated with Industry 4.0 concept and what are the benefits of such an integration are still open issues. Therefore, this study investigates how to implement the Industry 4.0 concept for the specific case of mass customization industry and, by using modeling and simulation, proposes a quantification of the benefits of such implementation. Implementing Industry 4.0 solutions requires high level of investments, and there is a great need of research that outlines its quantifiable benefits to justify the investments. To the aim of the research, two conceptual models, one integrating Industry 4.0 and mass customization and one featuring only mass customization, have been developed. Afterward, these two models have been simulated in FlexSim software in order to measure the performance. The results obtained seem to be extremely favorable for the implementation of Industry 4.0 solutions on mass customization systems. Significant improvement in product completion rate on time, customer satisfaction rate, utilization of equipment, and waiting time in queues has been observed. This study will help mass customization industries to understand the opportunities and criticalities concerned with the implementation of this concept.

Mass customisation (MC) is considered to be an important competitive tool to increase the performance of manufacturers. Due to the importance of MC as part of the manufacturing process, there is an increasing amount of research devoted to exploring the nature of MC and how to effectively implement MC processes. Based on the theory of complementary assets, this study investigates the relationships between different MC practices and the effects of these practices on the firm's financial performance. In this study, simultaneous equation modelling and hierarchical regression analysis are applied to data collected from a large-scale survey in China. The results show that different MC practices positively affect each other, and that the interactions between the MC practices positively influence a firm's financial performance. This indicates that the complementary adoption of MC practices is important for a firm's success, requiring the simultaneous deployment of elicitation, process-flexible technology and logistics practices.

This paper proposes a method which is to achieve an optimal scheduling and stock allocation planning simultaneously using a combinatorial auction under mass customization system. Proposal method decides a production scheduling and material stock allocation planning to aim minimizing the delay from acceptable delivery time. A numerical example is then discussed to demonstrate its suitability in obtaining an optimal plan under negotiations between manufacturer and customers.

The growth in product variety has been accelerating in almost all product categories over the last four decades. Providing high levels of variety and customisation is challenging for many producers. Here the range and diversity of order fulfilment approaches available to producers to respond are examined critically. A continuum of six fulfilment approaches is presented, encompassing both traditional approaches and those that have emerged more recently. The new integrated perspective focuses on how a producer can respond to provide relevant product variety and customisation. Demand-side and supply-side factors influencing the need for greater flexibility in order fulfilment systems are identified and the need to balance both is emphasised. Two specific approaches – mass customisation and open pipeline systems – are analysed in detail. The range of order fulfilment approaches is considered in the context of postponement and production system decoupling. Challenges in two sectors – the clothing sector and the automotive sector – are analysed. The factors affecting the choice of order fulfilment approach are discussed. Producers experiencing the competitive pressures to provide greater levels of variety and customisation need to consider the full range and diversity of order fulfilment approaches discussed here.

Operational Classification and Method for Reconfiguration & Recommissioning of Changeable Manufacturing Systems on System Level

In modern conditions, to ensure the successful implementation of any activity, it is necessary to perform high-quality and efficient forecasting of current processes. The scope of application is expanding, making the task of forecasting even more important and complex. The increasing role of forecasting in the modern world has given rise to over a hundred models and methods of forecasting. For this reason, the challenge becomes to select the optimal variant of forecasting the process or system under study. In the present article, the main mathematical methods of forecasting time series are analyzed and their advantages and disadvantages described. Criteria for the accuracy of forecasting models are defined. Practical application of various models is considered. The possibilities for implementing forecasting models are investigated. The capabilities of the Python programming language for developing forecasting models are evaluated. The paper solves the problem of constructing a weighted-average forecast, which consists of several individual forecasts. Original forecasting models that were used in the combination included Arima, gradient boosting and a fully connected feed-forward neural network. Neural networks are growing more relevant today, as they enable forecasting in the event of a crisis and uncertainty. During the implementation of the programming solution, the mean absolute errors were computed for each forecasting method as well as for the weighted-average forecast. #COMESYSO1120.

In the last decade, the use of earth in construction has become increasingly widespread in many countries. Building with earth can contribute to sustainable development by reducing environmental impact compared with other building materials or systems. This new consciousness has given rise to a growth in the number of earth building standards in recent years, although, in absolute terms, the number is very small compared with other typical building materials and systems. Thirty-nine different earth building standards from 19 different countries were examined. The standards provide varying degrees of technical information. With regard to their scope of application, the documents can be classified into three types, each of them dealing with a particular aspect: soil classification, earth building materials and earth construction systems. In Germany, a revival of building with earth first came about in the 1980s as an awareness of ecological criteria grew. A product of this development was the elaboration of an earth building standard, the 'Lehmbau Regeln' by the Dachverband Lehm e.V., the German national earth building association. That part of the 'Lehmbau Regeln' concerning earth blocks and earth mortars was adapted to the circumstances of national DIN/European building codes and published in August 2013 as DIN 18945-47.

A Reverse Blending based supply chain for mass customization of green fertilizers

This paper presents a systematic literature review that reflects the current state of research in the field of algorithms and models for map generalization, the existing solutions for automatic (tactile) map generation, as well as good practices for designing spatial databases for the purposes of automatic map development. A total number of over 500 primary studies were screened in order to identify the most relevant research on automatic (tactile) map generation from the last decade. The reviewed papers revealed many existing solutions in the field of automatic map production, as well as algorithms (e.g., Douglas–Peucker, Visvalingam–Whyatt) and models (e.g., GAEL, CartACom) for data generalization that might be used to transform traditional spatial data into the haptic form, suitable for blind and visually impaired people. However, it turns out that a comprehensive solution for automatic tactile map generation does not exist.

PurposeThe purpose of this paper is to develop an agility evaluation approach to determine the most suitable agile system for implementing mass customization (MC) strategies. Evaluating the alternatives and comparing across them, the best practices of the efficient organization can be identified and transferred to different organizations.Design/methodology/approachGrey relation approach is a simple mathematical technique useful in situations where the information is not known precisely. Grey relation approach has been applied to measure the agility of various organizations based on agile entities and accordingly the organizations are ranked. The ranking so obtained is compared with the ranking obtained by a popular multi‐attribute decision making (MADM) process known as Fuzzy TOPSIS (technique for order preference by similarity to ideal solution) to test the robustness of the proposed method. It is to be noted that grey theory considers the condition of the fuzziness and can deal flexibly with the fuzziness situation.FindingsIt is demonstrated that the grey approach is an appropriate method for solving MADM problems in an uncertain situation with less computational efforts. The alternatives can easily be benchmarked and the best agile system can be selected. As the ranking obtained through grey relation approach closely agree with the ranking found from Fuzzy TOPSIS method, the robustness of the proposed approach is validated. Both the methods lead to choosing a suitable agile system related to mass customization.Research limitations/implicationsIn this paper, the proposed approach has been compared with Fuzzy TOPSIS method to test the robustness of the method. Other MADM approaches may be used for comparison purpose to gain insight into the methodology of the proposed approach.Originality/valueAn alternative approach for MADM is proposed to obtain good decisions in an uncertain environment and used for agility evaluation in selected organizations. As agile manufacturing is relatively a new concept, certain and complete information on systems are not available. In such situations, the proposed method can deal with the issue conveniently and results in workable solutions.

Although the automotive industry is relatively efficient in managing the production line, mass customization remains a major challenge. The difficulty lies in the establishment of channels to support customer feedback and interaction in directing the planning and design new products. There is thus a big gap between user requirements and product features. We explore the development of a platform for bridging this “semantic gap” between user needs and the decision-making process new product planners and designers. This paper presents the framework for this platform, which will then serve as a support for a mass customization system.

The popularisation of mass customization and the need for integration of the user needs into the design, production and marketing phases has called for more innovative methods to be introduced into this area. At present the continuous growth of the world wide web and its rapid integration into people’s everyday lives and the popularisation of new technologies such as ubiquitous computing making possible the computing everywhere paradigm, offers a more desirable alternative for vendors in reaching their customers using more innovative techniques in an attempt to provide each customer with a one-to-one design, manufacturing and marketing service. The integration of ubiquitous computing technologies with machine learning and data mining techniques, which has been popular in personalization techniques, will serve to bring about innovative changes in this area. In future years this may revolutionise the way in which vendors can reach their customers offering every customer a tailored one-to-one service from design, to manufacturing, to delivery. This chapter will present the state of the art techniques to enable the combination of machine learning, data mining and ubiquitous computing technologies which will serve to provide innovative techniques applications and user interfaces for mass customization systems. This is currently a field of intense research and development activity and some technologies are already on the path to practical application. This chapter will present a state of the art survey of these technologies and their applications.

In order to realize furniture industry development of higher level, higher quality, higher level, the paper study custom furniture products produced through the use of lean production organization and management, group technology and production organization, etc. can be achieved in implementation of mass customization systems of furniture production.

Web-based 3D toolkits create a virtual product environment in Mass Customization (MC) sites, allowing consumers to design their own products or services. A large amount of effort has clearly been expended to build a number of commercial web-based 3D MC systems, but few studies have been conducted to evaluate them, especially their toolkit design. In this paper we take a practical perspective and apply an Online 3D Mass Customization Toolkit Evaluation Model, proposed in our previous study [25], to evaluate four commercial web-based 3D toolkits. This evaluation indicates that current 3D toolkits are still at an early development stage and there are opportunities for improvement. We therefore conclude by identifying a number of open research questions in terms of solution space design, interaction design, enabling technologies and individual differences.