Publications

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Generative process planning describes methods process engineers use to modify manufacturing/process plans after designs are complete. A completed design may be the result from the introduction of a new product based on an old design, an assembly upgrade, or modified product designs used for a family of similar products. An engineer designs an assembly and then creates plans capturing manufacturing processes, including assembly sequences, component joining methods, part costs, labor costs, etc. When new products originate as a result of an upgrade, component geometry may change, and/or additional components and subassemblies may be added to or are omitted from the original design. As a result process engineers are forced to create new plans. This is further complicated by the fact that the process engineer is forced to manually generate these plans for each product upgrade. To generate new assembly plans for product upgrades, engineers must manually re-specify the manufacturing plan selection criteria and re-run the planners. To remedy this problem, special-purpose assembly planning algorithms have been developed to automatically recognize design modifications and automatically apply previously defined manufacturing plan selection criteria and constraints.

Sandia's Archimedes 3.0{copyright} Automated Assembly Analysis System has been applied successfully to several large industrial and weapon assemblies. These have included Sandia assemblies such as portions of the B61 bomb, and assemblies from external customers such as Cummins Engine Inc., Raytheon (formerly Hughes) Missile Systems and Sikorsky Aircraft. While Archimedes 3.0{copyright} represents the state-of-the-art in automated assembly planning software, applications of the software made prior to the technological advancements presented here showed several limitations of the system, and identified the need for extensive modifications to support practical analysis of assemblies with several hundred to a few thousand parts. It was believed that there was substantial potential for enhancing Archimedes 3.0{copyright} to routinely handle much larger models and/or to handle more modestly sized assemblies more efficiently. Such a mature assembly analysis capability was needed to support routine application to industrial assemblies that overstressed the system, such as full nuclear weapon assemblies or full-scale aerospace or military vehicles.

Designing products for easy assembly and disassembly during their entire life cycles for purposes including product assembly, product upgrade, product servicing and repair, and product disposal is a process that involves many disciplines. In addition, finding the best solution often involves considering the design as a whole and by considering its intended life cycle. Different goals and manufacturing plan selection criteria, as compared to initial assembly, require re-visiting significant fundamental assumptions and methods that underlie current assembly planning techniques. Previous work in this area has been limited to either academic studies of issues in assembly planning or to applied studies of life cycle assembly processes that give no attention to automatic planning. It is believed that merging these two areas will result in a much greater ability to design for, optimize, and analyze the cycle assembly processes. The study of assembly planning is at the very heart of manufacturing research facilities and academic engineering institutions; and, in recent years a number of significant advances in the field of assembly planning have been made. These advances have ranged from the development of automated assembly planning systems, such as Sandia's Automated Assembly Analysis System Archimedes 3.0{copyright}, to the startling revolution in microprocessors and computer-controlled production tools such as computer-aided design (CAD), computer-aided manufacturing (CAM), flexible manufacturing systems (EMS), and computer-integrated manufacturing (CIM). These results have kindled considerable interest in the study of algorithms for life cycle related assembly processes and have blossomed into a field of intense interest. The intent of this manuscript is to bring together the fundamental results in this area, so that the unifying principles and underlying concepts of algorithm design may more easily be implemented in practice.

Automatic assembly sequencing and visualization tools are valuable in determining the best assembly sequences, but without Human Factors and Figure Models (HFFMs) it is difficult to evaluate or visualize human interaction. In industry, accelerating technological advances and shorter market windows have forced companies to turn to an agile manufacturing paradigm. This trend has promoted computerized automation of product design and manufacturing processes, such as automated assembly planning. However, all automated assembly planning software tools assume that the individual components fly into their assembled configuration and generate what appear to be a perfectly valid operations, but in reality the operations cannot physically be carried out by a human. Similarly, human figure modeling algorithms may indicate that assembly operations are not feasible and consequently force design modifications; however, if they had the capability to quickly generate alternative assembly sequences, they might have identified a feasible solution. To solve this problem HFFMs must be integrated with automated assembly planning to allow engineers to verify that assembly operations are possible and to see ways to make the designs even better. Factories will very likely put humans and robots together in cooperative environments to meet the demands for customized products, for purposes including robotic and automated assembly. For robots to work harmoniously within an integrated environment with humans the robots must have cooperative operational skills. For example, in a human only environment, humans may tolerate collisions with one another if they did not cause much pain. This level of tolerance may or may not apply to robot-human environments. Humans expect that robots will be able to operate and navigate in their environments without collisions or interference. The ability to accomplish this is linked to the sensing capabilities available. Current work in the field of cooperative automation has shown the effectiveness of humans and machines directly interacting to perform tasks. To continue to advance this area of robotics, effective means need to be developed to allow natural ways for people to communicate and cooperate with robots just as they do with one another.

This paper presents a practical approach for integrating automatically designed fixtures with automated assembly planning. Product assembly problems vary widely; here the focus is on assemblies that are characterized by a single base part to which a number of smaller parts and subassemblies are attached. This method starts with three-dimension at CAD descriptions of an assembly whose assembly tasks require a fixture to hold the base part. It then combines algorithms that automatically design assembly pallets to hold the base part with algorithms that automatically generate assembly sequences. The designed fixtures rigidly constrain and locate the part, obey task constraints, are robust to part shape variations, are easy to load, and are economical to produce. The algorithm is guaranteed to find the global optimum solution that satisfies these and other pragmatic conditions. The assembly planner consists of four main elements: a user interface, a constraint system, a search engine, and an animation module. The planner expresses all constraints at a sequencing level, specifying orders and conditions on part mating operations in a number of ways. Fast replanning enables an interactive plan-view-constrain-replan cycle that aids in constrain discovery and documentation. The combined algorithms guarantee that the fixture will hold the base part without interfering with any of the assembly operations. This paper presents an overview of the planners, the integration approach, and the results of the integrated algorithms applied to several practical manufacturing problems. For these problems initial high-quality fixture designs and assembly sequences are generated in a matter of minutes with global optimum solutions identified in just over an hour.

Automatic assembly sequencing and visualization tools are valuable in determining the best assembly sequences, but without Human Factors and Figure Models (HFFMs) it is difficult to evaluate or visualize human interaction. In industry, accelerating technological advances and shorter market windows have forced companies to turn to an agile manufacturing paradigm. This trend has promoted computerized automation of product design and manufacturing processes, such as automated assembly planning. However, all automated assembly planning software tools assume that the individual components fly into their assembled configuration and generate what appear to be perfectly valid operations, but in reality some operations cannot physically be carried out by a human. For example, the use of a ratchet may be reasoned feasible for an assembly operation; however, when a hand is placed on the tool the operation is no longer feasible, perhaps because of inaccessibility, insufficient strength or human interference with assembly components. Similarly, human figure modeling algorithms may indicate that assembly operations are not feasible and consequently force design modifications, however, if they had the capability to quickly generate alternative assembly sequences, they might have identified a feasible solution. To solve this problem, HFFMs must be integrated with automated assembly planning which allows engineers to quickly verify that assembly operations are possible and to see ways to make the designs even better. This paper presents a framework for integrating geometry-based assembly planning algorithms with commercially available human figure modeling software packages. Experimental results to selected applications along with lessons learned are presented.

Constraints on assembly plans vary depending on product, assembly facility, assembly volume, and many other factors. Assembly costs and other measures to optimize vary just as widely. To be effective, computer-aided assembly planning systems must allow users to express the plan selection criteria that appIy to their products and production environments. We begin this article by surveying the types of user criteria, both constraints and quality measures, that have been accepted by assembly planning systems to date. The survey is organized along several dimensions, including strategic vs. tactical criteria; manufacturing requirements VS. requirements of the automated planning process itself and the information needed to assess compliance with each criterion. The latter strongly influences the efficiency of planning. We then focus on constraints. We describe a framework to support a wide variety of user constraints for intuitive and efficient assembly planning. Our framework expresses all constraints on a sequencing level, specifying orders and conditions on part mating operations in a number of ways. Constraints are implemented as simple procedures that either accept or reject assembly operations proposed by the planner. For efficiency, some constraints are supplemented with special-purpose modifications to the planner's algorithms. Fast replanning enables an interactive plan-view-constrain-replan cycle that aids in constraint discovery and documentation. We describe an implementation of the framework in a computer-aided assembly planning system and experiments applying the system to a number of complex assemblies, including one with 472 parts.

At the 1995 IEEE Symposium on Assembly and Task Planning, Sandia National Laboratories introduced the Archimedes 2 Software Tool [2]. The system was described as a second-generation assembly planning system that allowed preliminmy application of awembly planning for industry, while solidly supporting further research in planning techniques. Sandia has worked closely with indust~ and academia over the last four years. The results of these working relationships have bridged a gap for the next generation in assembly planning. Zke goal of this paper is to share Sandia 's technological advancements in assembly planning over the last four years and the impact these advancements have made on the manufacturing communip.

When a product concept emerges, the manufacturing engineer is asked to sketch out a production strategy and estimate its cost. The engineer is given an initial product design, along with a schedule of expected production volumes. The engineer then determines the best approach to manufacturing the product, comparing a variey of alternative production strategies. The engineer must consider capital cost, operating cost, lead-time, and other issues in an attempt to maximize pro$ts. After making these basic choices and sketching the design of overall production, the engineer produces estimates of the required capital, operating costs, and production capacity. 177is process may iterate as the product design is refined in order to improve its pe~ormance or manufacturability. The focus of this paper is on the development of computer tools to aid manufacturing engineers in their decision-making processes. This computer sof~are tool provides aj?amework in which accurate cost estimates can be seamlessly derivedfiom design requirements at the start of any engineering project. Z+e result is faster cycle times through first-pass success; lower ll~e cycie cost due to requirements-driven design and accurate cost estimates derived early in the process.

Designing products for ~ assembly and disassembly during its entire Iifecycle for purposes including service, field repair, upgrade, and disposal is a process that involves many disciplines. In additiou finding the best solution often involves considering the design as a whole and by considering its intended Iifecycle. DifFerent goals and cortstmints (compared to initial assembly) require us to re-visit the significant fi,mdamental assumptions and methods that underlie current assembly planning techniques. Previous work in this area has been limited to either academic studies of assembly planning or applied studies of lifecycle assembly processes, which give no attention to automatic planning. It is believed that merging these two areas will result in a much greater ability to design for, analyze, and optimize the disassembly and assembly processes.

Many manufacturing companies today expend more effort on upgrade and disposal projects than on clean-slate design, and this trend is expected to become more prevalent in coming years. However, commercial CAD tools are better suited to initial product design than to the product`s full life cycle. Computer-aided analysis, optimization, and visualization of life cycle assembly processes based on the product CAD data can help ensure accuracy and reduce effort expended in planning these processes for existing products, as well as provide design-for-lifecycle analysis for new designs. To be effective, computer aided assembly planning systems must allow users to express the plan selection criteria that apply to their companies and products as well as to the life cycles of their products. Designing products for easy assembly and disassembly during its entire life cycle for purposes including service, field repair, upgrade, and disposal is a process that involves many disciplines. In addition, finding the best solution often involves considering the design as a whole and by considering its intended life cycle. Different goals and constraints (compared to initial assembly) require one to re-visit the significant fundamental assumptions and methods that underlie current assembly planning techniques. Previous work in this area has been limited to either academic studies of issues in assembly planning or applied studies of life cycle assembly processes, which give no attention to automatic planning. It is believed that merging these two areas will result in a much greater ability to design for; optimize, and analyze life cycle assembly processes.