Lean manual assembly 4.0: A systematic review

In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic

Application of lean scheduling and production control in non-repetitive manufacturing systems using intelligent agent decision support

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Lean Manufacturing (LM) is widely accepted as a world-class manufacturing paradigm, its currency and superiority are manifested in numerous recent success stories. Most lean tools including Just-in-Time (JIT) were designed for repetitive serial production systems. This resulted in a substantial stream of research which dismissed a priori the suitability of LM for non-repetitive non-serial job-shops. The extension of LM into non-repetitive production systems is opposed on the basis of the sheer complexity of applying JIT pull production control in non-repetitive systems fabricating a high variety of products. However, the application of LM in job-shops is not unexplored. Studies proposing the extension of leanness into non-repetitive production systems have promoted the modification of pull control mechanisms or reconfiguration of job-shops into cellular manufacturing systems. This thesis sought to address the shortcomings of the aforementioned approaches. The contribution of this thesis to knowledge in the field of production and operations management is threefold: Firstly, a Multi-Agent System (MAS) is designed to directly apply pull production control to a good approximation of a real-life job-shop. The scale and complexity of the developed MAS prove that the application of pull production control in non-repetitive manufacturing systems is challenging, perplex and laborious. Secondly, the thesis examines three pull production control mechanisms namely, Kanban, Base Stock and Constant Work-in-Process (CONWIP) which it enhances so as to prevent system deadlocks, an issue largely unaddressed in the relevant literature. Having successfully tested the transferability of pull production control to non-repetitive manufacturing, the third contribution of this thesis is that it uses experimental and empirical data to examine the impact of pull production control on job-shop performance. The thesis identifies issues resulting from the application of pull control in job-shops which have implications for industry practice and concludes by outlining further research that can be undertaken in this direction

Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems

This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book

Productivity and flexibility improvement of assembly lines for high-mix low-volume production. A white goods industry case

Las tendencias globales de la personalización e individualización en masa impulsan la producción industrial en serie corta y variada; y por tanto una gran variedad de productos en pequeñas cantidades. Por ello, la customización en masa precisa de sistemas de ensamblaje que sean a la vez altamente productivos y flexibles, a diferencia de la tradicional oposición entre ambas características. La llamada cuarta revolución industrial trae diversas tecnologías habilitadoras que podrían ser útiles para abordar este problema. Sin embargo, las metodologías para implementar el ensamblaje 4.0 todavía no han sido resueltas. De hecho, para aprovechar todas las ventajas potenciales de la Industria 4.0, es necesario contar con un nivel previo de excelencia operacional y un análisis holístico de los sistemas productivos. Esta tesis tiene como objetivo entender y definir cómo mejorar la productividad y la flexibilidad de las operaciones de montaje en serie corta y variada.Esta meta se ha dividido en tres objetivos. El primer objetivo consiste en comprender las relaciones entre la Industria 4.0 y las operaciones de ensamblaje, así como sus implicaciones para los operarios. El segundo objetivo consiste en desarrollar una metodología y las herramientas necesarias para evaluar el rendimiento de diferentes configuraciones de cadenas de ensamblaje. El último objetivo consiste en el diseño de sistemas de ensamblaje que permitan incrementar su productividad al menos un 25 %, produciendo en serie corta y variada, mediante la combinación de puestos de montaje manual y estaciones automatizadas.Para abordar la fase de comprensión y definición del problema, se llevó a cabo una revisión bibliográfica sistemática y se desarrolló un marco conceptual para el Ensamblaje 4.0. Se desarrollaron, verificaron y validaron dos herramientas de evaluación del rendimiento: un modelo matemático analítico y varios modelos de simulación por eventos discretos. Para la verificación, y como punto de partida para los análisis, se ha utilizado un caso de estudio industrial de un fabricante global de electrodomésticos. Se han empleado múltiples escenarios de simulación y técnicas de diseño de experimentos para investigar tres cuestiones clave.En primer lugar, se identificaron los factores más críticos para el rendimiento de líneas de montaje manuales multi-modelo. En segundo lugar, se analizó el rendimiento de líneas de montaje semiautomáticas paralelas con operarios móviles en comparación con líneas semiautomáticas o manuales con operarios fijos, empleando diversos escenarios de demanda en serie corta y variada. Por último, se investigó el uso de trenes milkrun para la logística interna de líneas de ensamblaje multi-modelo bajo la influencia de perturbaciones.Los resultados de las simulaciones muestran que las líneas paralelas con operarios móviles pueden superar a las de operarios fijos en cualquier escenario de demanda, alcanzando como mínimo el objetivo de mejorar la productividad en un 25% o más. También permiten reducir cómodamente el número de operarios trabajando en la línea sin afectar negativamente al equilibrado de la misma, posibilitando la producción eficiente de bajo volumen. Los resultados de las simulaciones de logística interna indican que los milkrun pueden proteger las líneas de ensamblaje de las perturbaciones originadas en procesos aguas arriba.Futuras líneas de investigación en base a los resultados obtenidos en esta tesis podrían incluir la expansión e integración de los modelos de simulación actuales para analizar las cadenas de montaje paralelas con operarios móviles incorporando logística, averías y mantenimiento, problemas de control de calidad y políticas de gestión de los retrabajos. Otra línea podría ser el uso de diferentes herramienta para el análisis del desempeño como, por ejemplo, técnicas de programación de la producción que permitan evaluar el desempeño operacional de diferentes configuraciones de cadenas de montaje con operarios móviles, tanto en términos de automatización como de organización en planta. Podrían incorporarse tecnologías de la Industria 4.0 a los modelos de simulación para evaluar su impacto operacional global ¿como cobots para ensamblaje o para la manipulación de materiales, realidad aumentada para el apoyo cognitivo a los operarios, o AGVs para la conducciónde los trenes milkrun. Por último, el trabajo presentado en esta tesis acerca las líneas de ensamblaje semiautomáticas con operarios móviles a su implementación industrial.<br /

A Resilient and Effective Task Scheduling Approach for Industrial Human-Robot Collaboration

Effective task scheduling in human-robot collaboration (HRC) scenarios is one of the great challenges of collaborative robotics. The shared workspace inside an industrial setting brings a lot of uncertainties that cannot be foreseen. A prior offline task scheduling strategy is ineffective in dealing with these uncertainties. In this paper, a novel online framework to achieve a resilient and reliable task schedule is presented. The framework can deal with deviations that occur during operation, different operator skills, error by the human or robot, and substitution of actors, while maintaining an efficient schedule by promoting parallel human-robot work. First, the collaborative job and the possible deviations are represented by AND/OR graphs. Subsequently, the proposed architecture chooses the most suitable path to improve the collaboration. If some failures occur, the AND/OR graph is adapted locally, allowing the collaboration to be completed. The framework is validated in an industrial assembly scenario with a Franka Emika Panda collaborative robot

Assembly Line

An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line

Mass Production Processes

It is always hard to set manufacturing systems to produce large quantities of standardized parts. Controlling these mass production lines needs deep knowledge, hard experience, and the required related tools as well. The use of modern methods and techniques to produce a large quantity of products within productive manufacturing processes provides improvements in manufacturing costs and product quality. In order to serve these purposes, this book aims to reflect on the advanced manufacturing systems of different alloys in production with related components and automation technologies. Additionally, it focuses on mass production processes designed according to Industry 4.0 considering different kinds of quality and improvement works in mass production systems for high productive and sustainable manufacturing. This book may be interesting to researchers, industrial employees, or any other partners who work for better quality manufacturing at any stage of the mass production processes