Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

QUALITY ANALYSIS IN FLEXIBLE MANUFACTURING SYSTEMS WITH BATCH PRODUCTIONS

To improve product quality and reduce cost, batch production is often implemented in many exible manufacturing systems. However, the current literature does not provide any method to analyze the quality performance in a flexible manufacturing system with batch production. In this research, we present an analytical method with closed-form formula to evaluate the quality performance in such systems. Based on the model, we discover and investigate monotonic and non-monotonic properties in quality to provide practical guidance for operation management. To improve product quality, we introduce the notions of quality improvability with respect to product sequencing. In addition, we develop the indicators for quality improvability based on the data available on the factory floor rather than complicated calculations. We define the bottleneck sequence and bottleneck transition as the ones that impede quality in the strongest manner, investigate the sensitivity of quality performance with respect to sequences and transitions, and propose quality bottleneck sequence and transition indicators based on the measured data. Finally, we provide a case study at an automotive paint shop to show how this method is applied to improve paint quality. Moreover, we explore a potential application to reduce energy consumption and atmospheric emissions at automotive paint shops. By selecting appropriate batch and sequence policies, the paint quality can be improved and repaints can be reduced so that less material and energy will be consumed, and less atmospheric emissions will be generated. It is shown that such scheduling and control method can lead to significant energy savings and emission reduction with no extra investment nor changes to existing painting processes. The successful development of such method would open up a new area in manufacturing systems research and contribute to establish a solid foundation for an integrated study on productivity, quality and exibility. In addition, it will provide production engineers and operation managers a quantitative tool for continuous improvement on product quality in flexible manufacturing environmen

Heuristic Solutions for Loading in Flexible Manufacturing Systems

Production planning in flexible manufacturing system deals with the efficient organization of the production resources in order to meet a given production schedule. It is a complex problem and typically leads to several hierarchical subproblems that need to be solved sequentially or simultaneously. Loading is one of the planning subproblems that has to addressed. It involves assigning the necessary operations and tools among the various machines in some optimal fashion to achieve the production of all selected part types. In this paper, we first formulate the loading problem as a 0-1 mixed integer program and then propose heuristic procedures based on Lagrangian relaxation and tabu search to solve the problem. Computational results are presented for all the algorithms and finally, conclusions drawn based on the results are discussed

Exploitation of the knowledge of the final demand in the piloting of a logistics chain.

The transition from synchronous supplies to synchronous production represent a possible alternative to the neighbourhood logistics configurations, especially in the automotive industry. It allows to gain, on certain conditions, efficiency and more manoeuvrability faced with a strong variability of the demand on the supply chain. The utilization of the Order Penetration Point (OPP) will introduce problems in piloting production between clients and suppliers processes. This article is based on several working assumptions which form an algorithm for the resolution of this problem resulting from an analysis of two industrial cases with stochastic models.synchronous production; supply chain; anticipation; piloting of flows; order penetration point; kanban;

Scheduling Coordination in a Supply Chain Using Advance Demand Information.

In an environment of mass customization where demand information can be placed in advance with sequencing orders, the question of the best use of this information arises in a supply chain. This situation led the authors to analyze the efficiency of current mechanisms of scheduling coordination when suppliers' processes are not completely reliable. Policies such as periodic replenishment or the kanban system, characterized by a replacement of the items to consume, cannot be exploited effectively with the current rules. This paper presents and justifies new scheduling coordination rules allowing synchronous production in an unreliable environment. This new approach has been benchmarked in the automotive industry as an appropriate method to avoid stockouts and decrease the safety stock.Chaîne logistique; Synchronisation de la production dans une chaîne logistique; kanban; Production synchrone; Point de Pénétration de commande;

AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

A Systematic Approach to Quality Oriented Product Sequencing for Multistage Manufacturing Systems

Product sequencing is one way to reduce cost and improve product quality for multistage manufacturing systems (MMS). However, systematically evaluating the influence of product sequence on quality performance for MMS is still a challenge. By considering the rate of incoming conforming product, manufacturing system quality transition between batch to batch, and quality propagation along stages, this paper investigates the appropriate batch policies and product sequencing for MMS so that satisfied quality performance can be achieved. A model to analyze the relationship between the product sequencing and quality performance is conducted just by using the quality inspection data and the complex engineering knowledge used in the variation method is avoided. Based on Markov Chain processes methodology, quality performance is modeled as a function of transition states jointly determined by multistage condition, product sequencing, incoming part quality, and propagation of the rate of conforming products among multistage. Quality related batch strategies are discussed for optimal quality performance. Two kinds of quality efficiency are put forward to facilitate the modeling and the discussion. The results of the model will lead to guidelines for quality management in multistage manufacturing systems

A Neighborhood Search for Sequence-dependent Setup Time in Flow Shop Fabrics Making of Textile Industry

Abstract This paper proposes a neighborhood search to solve scheduling for fabrics making in a textile industry. The production process consists of three production stages from spinning, weaving, and dyeing. All stages have one processor. Setup time between two consecutive jobs with different color is considered. This paper also proposes attribute’s decomposition of a single job to classify available jobs to be processed and to consider setup time between two consecutive jobs. Neighborhood search (NS) algorithm is proposed in which the permutation of set of jobs with same attribute and the permutation among set of jobs is conducted. Solution obtained from neighborhood search, which might be trapped in local solution, then is compared with other known optimal methods

A survey of scheduling problems with setup times or costs

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

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 /