High Throughput Production Processing of Five- (5) Axis Aluminum Components (HITHRU)

DoD Participants:  U.S. Air Force – Warner Robins Air Logistics Center; U.S. Navy – Fleet Readiness Center East

Project Driver and Objectives

The United States Department of Defense now sustains current weapon systems well past their originally intended life. The effect is a need for unpredictable repair or replacement of components that are not in the supply system, which produces requirements for low job order quantity; short lead time orders that do not interest private industry. In many cases, digital data is not available for these components, requiring that three-dimensional (3D) solid models and numerical control (NC) programs be developed for component manufacture. The resulting long acquisition cycle grounds badly needed aircraft.

Other, non-CTMA programs address the reverse engineering of parts and the creation of solid models. The objectives of this project were to:

·    Reduce by 50% NC programming time by developing and demonstrating a high-throughput 5-axis machining system that would program and produce first article and production parts from 3D solid models with a minimum of human intervention (programming and trouble shooting).

·    Increase the probability that the very first part produced would meet geometric and surface finish requirements.

·    Increase shop floor productivity by incorporating high productivity setup and machining methods.

An additional task to the project was approved in the Fall of 1999 to enhance the system via the creation of a new user interface. This would enable users to modify many of the rule sets online, within the system runtime environment and without need for C++ programming or the assistance of the vendor. The objective of this portion of the project was to empower users for modifications to the system knowledge base.

The HITHRU Project

The project addressed both shop floor and computer numerical control (CNC) programming productivity. Five- (5) axis feature recognition capability was added to the CIMPLEX system and the project team defined high-speed machining standards specifically tailored to aerospace aluminum components manufactured on a Cincinnati Machine Lancer V5 series vertical machining center using a standard set of carbide cutting tools. This greatly enhanced CIMPLEX system was renamed Cimskil^™.

The feature extraction rule set was defined by example. The industrial user partners and the depot partner selected example parts from among their component portfolios and offered design and manufacturing documentation to the team for the purpose of selecting a test part to drive development. The part selected was from Warner Robins Air Logistics Center (ALC).

Technology Answers analyzed features found on that part and used analysis results to guide the design of feature recognition rules. The success metric chosen was that the system should auto­matically (without user prompting) recognize at least 80% of typical aerospace features.

The process-planning rule set was defined partially by example from process best practices provided by participants and also by shop floor characterization of the dynamic characteristics of the machine, spindle and cutting tools selected for use in the project. The Cincinnati Machine Lancer V5 series vertical machining center with a 15,000 rpm, 35-hp HSK spindle was selected by the team as the demonstration machine. Partners provided lists of preferred carbide cutting tools and process practices, including spindle speed and table feed rates. Optimized metal removal processes, however, demand maximized metal removal rates, which in turn introduces the risk of harmful chatter. Chatter is a harmful phenomenon occurring when the dynamic characteristics of a machine tool, spindle, toolholder, and fixture align in frequency component with a harmonic of the cutting forces produced by the flutes of a cutting tool as it rotates. Avoiding chatter requires that cutting forces be mapped onto a graph of cutting force versus spindle rpm for a range of appropriate depth of cut choices so that chatter zones may be identified in advance. Cincinnati Machine performed all the necessary dynamic testing of the machine tool plus validation testing of the results. From all that data, Cincinnati Machine defined an algorithm that recommends optimized cutting parameters (spindle rpm, axial and radial depth of cut, and table feed rate). Note—the algorithm as implemented in this project can only work for aerospace aluminum parts produced on the Cincinnati Machine Lancer V5 series vertical machining center with a 15,000 rpm, 35-hp HSK spindle. However, the dynamic testing techniques are well known so other machines can be modeled to extend the benefits.

Combining automated feature recognition with automated process planning enabled the creation of CNC programs with greatly reduced effort. Since the resulting metal removal process was also optimized, overall productivity was increased. To gauge system effectiveness, the team planned to first evaluate effectiveness (level of automation) and accuracy (of geometric measurements) of the system by first making test parts at Cincinnati Machine and then running several trial parts through the Warner Robins ALC shop. The first effort would validate the system design for the test part, the second would test its effectiveness across several parts with different features and would also serve to gather real programming and shop floor production data for benchmarking process metrics against the legacy process. Unfortunately, Warner Robins ALC purchased and installed a Lancer V5 vertical machining center in late 2002; too late to accomplish the production validation task. To provide a backup process metrics evaluation, Sikorsky provided STEP models of about 40 production parts that Cincinnati Machine ran through Cimskil^™ and then made some parts in its shop.

Benefits

Benefits were quite clear from validation testing results. Several the Sikorsky parts are currently produced on 3- or 4-axis machine tools using more than two (2) setups and complex part-holding fixtures. The HITHRU process uses only two (2) setups (front side/back side) plus a considerably greater metal removal rate. The result was higher shop floor productivity. Process planning automation ranged from about 40 to greater than 80% for the Sikorsky test parts and shop floor productivity improvement ranged between 67 – 75%. True benchmarking of programming productivity increase proved impossible because no team member tracks CNC programming time by part number. To quantify metrics, the team asked expert programmers to estimate the time required for the validation parts as if they were contracting to perform the work. The admittedly not very scientific results (programmers will always overestimate the time required) indicated that programming productivity could increase by as much as 80 or as little as 50%.

Machine time cost savings are difficult to accurately model without data specific to a manufacturing operation. Programming costs savings are much easier to estimate and could range between $2,000 – 6,750 per part.

Depots report that on an average 15 – 20 parts of this type pass through their shops each month. The expected yearly savings could then be on the order of $360,000 – 1,620,000 per year.

Recommendations

Several recommendations for enhancements emerged during the course of this project:

·        Operating system support—recommend porting to Windows 2000

·        Multiple setup support—recommend that Cimskil^™ be modified to incorporate features that support multiple, complex setups

·        Additional materials—recommend that support for optimized metal removal process for materials other than aluminum be added

·        Probing cycle support—complex work-holding strategies demand the use of probing cycles to locate a coordinate reference point

·        Special controller function calls—many controllers embed very useful but non-standard special features

·        Integration with Macro Planning—recommend that Cimskil^™ be integrated with a macro planning system such as MetCAPP.

·        Multiple setup support—recommend that Cimskil^™ be modified to produce accurate solid models that reflect work in process after each completed operation

·        Integration with metrology planning—why not plan validation testing as well as the metal removal process

·        3D solid models of in-process part—components requiring multiple setups where the component is moved to different machines need to treat the result of one operation as the feed stock for the next, implying a future need for creating and archiving work in process models.

Machine tool libraries—Cimskil^™ incorporates mechanisms that allow users to extend the built-in machine tool library but a public library database of standard machines would save time and increase modeling accuracy.