Advanced Computer-Aided Fixture Design

Yiming (Kevin) Rong, Samuel Huang

• Publisher: Academic Press
• Year: 2005
• ISBN:
  9780080488271
• Topic: Technologie et ingénierie
• Subtopic: Génie mécanique

Fixtures--the component or assembly that holds a part undergoing machining--must be designed to fit the shape of that part and the type of machining being done. This book discusses the fundamentals of Computer-Aided Fixture Design (CAFD) techniques and covers fixture planning, fixture design (both modular and dedicated fixtures), fixture design verifications, and the overall integration with CAD/CAM. The book shows how CAFD may lead to a significant reduction of product and process development time and production cost, and how CAFD can increase quality assurance through simulation and science-based technical specification and cost estimation in business quoting, especially in current supplier-based manufacturing. It also provides case study examples.

• This book provides a total solution of CAFD, including planning, design, and design verification
• Practical and comprehensive theoretical analysis of fixturing from real industrial application projects
• Introduces the integration of fixture design and analysis with CAD/CAM so that detailed geometric information can be processed and complex fixture designs can be designed and analyzed

CHAPTER 1

Introduction

In a report on manufacturing technology, it was estimated that during the latter half of the 1990s the innovations in manufacturing technologies contributed nearly $1 trillion to the U.S. economy. Manufacturing is described as a cornerstone of the American economy. Manufacturing is critical to national security, defense, advanced technologies, precision machineries, and even our standard of living and creation of wealth. However, U.S. manufacturing is in decline. Between July of 2000 and December of 2003, 2.8 million manufacturing jobs disappeared. Since 1997, machine tool orders have decreased by 68%, from $8 billion to $3.35 billion, forcing 10% of the industry to close its doors (AMT, 2004).

U.S. manufacturers need to be able to compete in the global marketplace and have maximum agility in customizing their products for regional and personal preferences. The key is to develop enabling technologies to produce low- to medium-volume customized products with mass-production efficiency. Recent advances in flexible automation technologies, such as computer numerical controlled (CNC) machines, high-speed networking, and e-business, have made such quantum productivity jumps possible.

Computer-aided design and computer-aided manufacturing (CAD/CAM) tools have been used for product and process design for decades. As the power of computing continues to increase, the use of CAD/CAM has been ubiquitous, extending to the smallest shop and the most remote countries in the world. More recently, major CAD/CAM companies have been promoting product life-cycle management (PLM) in an attempt to integrate all product life-cycle functions, including engineering, purchasing, and manufacturing, into CAD-based systems. These PLM products have increased engineers’ productivity noticeably. However, the true potential of product life-cycle utilities is far from being fully realized. The problem is in part due to the complexity of product life-cycle functions. For example, in an internal survey Delphi found that a typical product drawing has 300 corresponding manufacturing documents. Manufacturing of a single component requires detailed consideration of candidate processes, tooling, fixtures, machines, and process parameters with complex interactions and constraints among them. Current PLM products are general-purpose tools and often involve many discrete modules or independent software that require extensive training and a great deal of manual input. The almost endless possibilities in tooling, work holding, and machines make general-purpose tools cumbersome and difficult to use.

To maximize overall manufacturing efficiency, the automotive industry, under extreme cost pressure and global competition, has developed elaborate processes to bring innovative products to market at minimum cost. These processes typically start with voice-of-customer (VOC), which defines product requirements. From these requirements, the product design is derived based on engineering principles and technical innovations. The product design dictates dimensions, surface finish, and tolerance requirements for each component. These requirements are subsequently used to determine appropriate processes, manufacturing systems, equipment design, build and runoff, and finally production launch and continuous improvement. Manufacturing system design (MSD) comes after capable processes are determined, but before hardware design and build are committed. MSD is the most opportunistic stage for optimization. It can help resolve design-for-manufacturing issues in making a product more manufacturable, and it is the right time to put all manufacturing options on the table and to determine the best solution before committing to a costly hardware build.

In facilitating the MSD process, it is important to take advantage of CAD technologies that help engineers visualize complex 3D geometric relationships of the workpiece, tooling, fixtures, machine components, tool paths, and so on toward detecting design errors, misfits, or interferences. Starting with a part family model, the manufacturing features are first recognized automatically and assigned with appropriate process parameters. Setup planning and machine tool/fixture selection and design can then be done based on the best-practice knowledge captured and represented in bill of processes (BOP). A series of verification functions is executed to validate the manufacturing plan. If all of these functions can be done within a few minutes or even hours, the MSD system can be a very effective tool for evaluating many process and manufacturing system concepts in an MSD workshop. Modeling complexity can be an issue. The key is to reduce system complexity by taking advantage of the similarities within a part family. By the same token, similarities in machines, fixtures, tooling, and machining features can be utilized to provide a structure to a solution to the problem. Within a well-defined problem or subproblem, verification functions can be used to provide feedback and toward identifying optimal solutions to a problem. The advanced optimization techniques, such as genetic algorithms, fuzzy logic, and neural network, can be applied to provide comprehensive optimization functions for fixture layout, locator and clamping layout, process sequencing, manufacturing system design, tool path, cycle time, cost, and so on. These optimization functions are especially useful in new product families for which little history or production experience exists to help derive an optimal solution by heuristic rules.

Manufacturing systems consist of manufacturing equipment laid out in sequence as a production line. Manufacturing equipment mainly includes machine tools, fixtures, and processing tools, which may be provided by different vendors. The manufacturing equipment contains the capabilities to generate geometric forms with the combination of the primary/feed motions provided by a machine tool and the cutting edge provided by a cutting tool; to process features in a certain position and orientations in one setup through the synthesis of machining table, spindle, and fixture; and to ensure production precision. Requirements regarding production time, cost, and quality; the process capabilities of available common equipments and, more complicatedly, customized equipments place major constraints on process planning and optimization.

A model for manufacturing equipment capability is very important in rapid MSD. Having established model of manufacturing equipment elements (e.g., machine, cutter, and fixtures), the overall capability of the subsystem can be established. Together with process information, the performance of the subsystem can be estimated with measures of quality, cycle time, and flexibility. Further studies are required to integrate manufacturing knowledge into the analysis of kinematics, stiffness, and accuracy information of machine tools, fixtures, and cutting tools so that mapping between manufacturing equipment capability data and manufacturing requirements identified at the part design stage can be performed.

Strategies regarding common manufacturing equipment exist for rapid MSD and optimization. Common manufacturing equipment is defined as manufacturing equipment qualified by current best practice for a family of parts in particular operations. Such equipment might be a machine, machine module, fixture, or combination of thereof. The commonality of equipment in processing similar parts simplifies the development of new equipment enhancing optimal performance. Via flexible combinations of common equipment, a variety of parts and processes can be dealt with based on similarities among those parts and processes. It has been proved that adapting common equipment to new production requirements can result in optimal solutions quickly.

Fixture design is also part of MSD. The objective of fixture design is to generate fixture configurations to hold parts firmly and accurately during manufacturing processes. Therefore, in rapid MSD, fixture design should be conducted at an early stage, in particular because conceptual fixture design contributes to the feasibility validation of MSD. Fixture design should also be verified to avoid later modification of the production system and processes, which can increase costs significantly. In other words, an intelligent fixture design is desired in MSD. An intelligent fixture design is necessary in adapting product and process designs while maintaining an optimal design for function and structural performance. An intelligent fixture design involves

• automated generation of a fixture design,

• use of best-practice knowledge in the design,

• reuse of best proven structural designs for specific functions,

• parametric design based on its correlation with required performance, and

• self-verification capability to ensure the design quality.

Although fixtures can be designed using CAD functions, a lack of scientific tools and a systematic approach in evaluating design performance reduces to a process of trial-and-errors, resulting in several problems. Such problems include the over-design of functions, which is very common and sometimes degrades performance; compromised quality of design before production; and the long lead time of fixture design, fabrication, and testing, which may take weeks if not months. Therefore, computer-aided fixture design (CAFD) has been motivated.

CAFD incorporates automated modular fixture design, where standard fixture components are used to construct desired fixture configurations (Rong 1999; Kow 1998; Brost 1996); dedicated fixture design with predefined fixture component types (An 1999; Chou 1993); rule-based and case-based reasoning (CBR) fixture design (Nee 1991; Kumar 1995; Pham 1990; Sun 1995; Boyle 2003); variation fixture design for part families (Rong 2003); and fixture design verification (Fuh 1994; Kang 2003). CAFD research has provided a methodology and concept-proven prototypes. How to make use of best-practice knowledge in fixture design and how to verify fixture design quality under various conditions remain areas of study. The applications of CAFD are still very limited because many operational constraints need to be considered.

CAFD has been a research focus at the Computer-aided Manufacturing Laboratory (CAM-Lab) at Worcester Polytechnic Institute (WPI), including association with Southern Illinois University at Carbondale, in collaboration with other research teams, for almost 15 years. Early work was presented in the first comprehensive book in the area of CAFD (Rong 1999). This book summarizes recent CAFD research work.

During such research it became clear that fixture design is part of manufacturing systems planning, in that fixtures are part of a manufacturing system. Fixture design is also part of manufacturing process verification, in that fixture performance contributes to the performance of manufacturing processes significantly, in both quality assurance and process stability, as well as to ease of process operation, which contributes to the efficiency of production cycle time and operation ergonomics. Therefore, this book takes the perspective that CAFD research is integrated with compu...