The evolution of cell formation problem methodologies based on recent studies (1997-2008): review and directions for future research

This paper presents a literature review of the cell formation (CF) problem concentrating on formulations proposed in the last decade. It refers to a number of solution approaches that have been employed for CF such as mathematical programming, heuristic and metaheuristic methodologies and artificial intelligence strategies. A comparison and evaluation of all methodologies is attempted and some shortcomings are highlighted. Finally, suggestions for future research are proposed useful for CF researchers

Part grouping for efficient process planning

A framework to provide automated part grouping has been investigated in order to overcome the limitations found in existing part grouping techniques. The work is targeted at: exploration of criteria for feature-based part grouping to make the process planning activity efficient; determination of the optimal number of part families in the part grouping process; development of an experimental hybrid process planning system (HYCAPP); investigation of the effects of improved part grouping on manufacturing cell design. The research work has explored the creation of a feature-based component data model and manufacturing system capability data model, and checked the limitations inherent in existing part grouping techniques i.e. part grouping: around methods; based on part geometry; based on machining processes; and based on machines. [Continues.

Integration of the Assessment and Design of Cellular Manufacturing System

نظام التصنيع الخلوي هو فلسفة تصنيع حديثة تعتمد على اسس مفهوم تكنولوجيا المجاميع. يؤدي نظام التصنيع الخلوي الى تحسين النوعية وزيادة الانتاجية. من خلال نظام التصنيع الخلوي يتم تجميع الاجزاء المنتجة في عوائل اعتمادا على التشابه فيما بينها في العوامل التصميمية او التصنيعية. وكذلك يتم تجميع المكائن التي تستخدم لانتاج تلك العوائل في مجاميع تسمى الخلايا. ان عملية التكامل تتم لفحص معلومات النظام الموجود مثل نظام التصنيع المعتمد على الوظيفة (Job shop) قبل تطبيق نظام التصنيع الخلوي (CM) . بناءا على ذلك فان الورقة الحالية تحاول اجراء هذا التكامل؛ حيث يتم في البداية فحص معلومات النظام الموجود في مرحلة التقييم ثم اجراء تكامل لنتائج هذه المرحلة مع المرحلة اللاحقة (مرحلة التصميم). في مرحلة التقييم تم استخدام مجموعة من الخطوات المتسلسلة. اما في مرحلة التصميم او تكوين الخلايا (CF) تم استخدام احد الطرق المعروفة وهي (ROC) لتكوين الخلايا والمجاميع. بعد ذلك استخدمت مجموعة من معايير الاداء لتقييم نظام التصنيع الخلوي المقترح. هذه المعايير هي (GE, GC%, Voids, EE, PE, MU). ولتحقيق هذا العمل تم اختيار ثلاثة مصفوفات من البحوث السابقة. ان الستراتيجية المتبعة في البحث الحالي ادت الى الحصول على نظام تصنيع خلوي كفوء وقد ادت النتائج التي تم الحصول عليها الى عدم ظهور اجزاء حرجة (EE) والى زيادة في قيمة معايير الاداء (MU, GC, GE) الى (84%, 84%, 92%) بالتسلسل.Cellular Manufacturing (CM) is a developed manufacturing philosophy that operates based on the principles of Groups Technology (GT) concept. It used to improve the quality and increase the productivity. Through CM, parts are grouped into families in view of their similarities in design /and or manufacturing features. Then again, machines likewise are gathered into cells to satisfy all the required processes on the families of parts. The integration was done with exam the manufacturing system, for example, job shop before applying the CM. Therefore, in the current paper an attempt was carried out firstly, to evaluate the presented production data, then to integrate the results of this step with the results of the next step, Cell Formation (CF) to acquire an effective CM system. In the evaluation part of the present paper, some hierarchical procedures were applied while in the design (cell formation) section, one of the well- known array based clustering method was utilized, this method known as Rank Order Clustering (ROC) and used to shape cells of machines and families of parts. However, some notable measures were utilized to assess the performance of the proposed CM, these measures are: grouping efficiency GE, grouping efficacy GC, voids, exceptional elements EE, percent of exceptional elements PE and machine utilization MU. To validate this work, three data sets (matrices) were chosen from the open literature. The strategy that followed lead to get a powerful CM solution. The outcomes demonstrated a missing of EE, increasing GE, GC, MU to 92%, 84%, 84% respectively

Cell formation problem - A Lagrangean relaxation to mathematical programming approach and a linear performance measure

Two topics in the part-machine cell formation problem are discussed: In the first part, a Lagrangean relaxation in a mathematical programming model is proposed to simultaneously set machines into groups and parts into families in a cellular manufacturing system. The objective of this model is to find the optimal number of cells while minimizing inter-cellular part moves and increasing utilization of machines within the cells. The method uses a 0-1 integer programming model. The Lagrangean relaxation relaxes the model through an iterative search. In the second part, we introduce a new performance measure and compare it to some known performance measures. The new measure preserved some important features of previous performance measures and overcomes a number of drawbacks. Both the measure and the model are applied to benchmark problems as well as randomly generated problems. The new measure and model are comparable to the existing models and measures

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

Computer-aided process planning (CAPP) SORICH

The last two decades have witnessed the increasing role of the computer in the process planning function. This has been further enhanced by the advent of the knowledge based expert system, and its impact on Computer Aided Process Planning (CAPP). CAPP has emerged as a strategic link between design and manufacture. This thesis discusses the various methods used in the process planning function. Group Technology (GT) plays a pivotal role in establishing CAPP. The utilization of Artificial Intelligence techniques in CAPP is listed. This study also presents an Interactive Software adaptive to product/part configuration variables

Using a design by features CAD system for process capability modelling

Process capability modelling offers a method of matching the shape, technological and cost capabilities of manufacturing equipment to the requirements of components, singly or as groups. This provides the basis of planning tools useful in the capital intensive business of the construction of new manufacturing facilities or the reconfiguration of existing ones. The success of this modelling approach is dependent upon having an appropriate representation of the design geometry. The representation must be such that all geometric inquiries raised by the process capability modelling are either explicitly held within some data representation or alternatively can be derived algorithmically by reference to a geometric model. The representation must also be capable of withstanding the rigours of use within the wider context of implementing an important part of the CAM interface within a CIM environment. This paper describes a feature-based representation based on a feature taxonomy which uses External Access Directions (EAD) as the characterizing aspect of geometry. These EADs become potential machining directions for a collection of features on a component, and are used as an essential link into generative process planning activities. The representation has been used in conjunction with process planning and process capability modelling applications. This paper concentrates on the latter, where the feature representation has been embedded within a proprietary geometric modeller which has been provided with a purpose-built user interface. A feature-based component model is created by the geometric modeller and accessed by functions which enable flexible component grouping and matching to process capability through the concept of a composite component. Subsequent process component grouping within the context of particular manufacturing systems strategies (cellular manufacture, flow-line, etc.) ultimately results in functional machine descriptions and variants

Data mining in manufacturing: a review based on the kind of knowledge

In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques

Reusable modelling and simulation of flexible manufacturing for next generation semiconductor manufacturing facilities

Automated material handling systems (AMHS) in 300 mm semiconductor manufacturing facilities may need to evolve faster than expected considering the high performance demands on these facilities. Reusable simulation models are needed to cope with the demands of this dynamic environment and to deliver answers to the industry much faster. One vision for intrabay AMHS is to link a small group of intrabay AMHS systems, within a full manufacturing facility, together using what is called a Merge/Diverge link. This promises better operational performance of the AMHS when compared to operating two dedicated AMHS systems, one for interbay transport and the other for intrabay handling. A generic tool for modelling and simulation of an intrabay AMHS (GTIA-M&S) is built, which utilises a library of different blocks representing the different components of any intrabay material handling system. GTIA-M&S provides a means for rapid building and analysis of an intrabay AMHS under different operating conditions. The ease of use of the tool means that inexpert users have the ability to generate good models. Models developed by the tool can be executed with the merge/diverge capability enabled or disabled to provide comparable solutions to production demands and to compare these two different configurations of intrabay AMHS using a single simulation model. Finally, results from simulation experiments on a model developed using the tool were very informative in that they include useful decision making data, which can now be used to further enhance and update the design and operational characteristics of the intrabay AMHS