NC Processing Research Articles

Flexible planning logic for technology planning

The ever-rising expectations of customers regarding quality and diversity of products require new products to be launched with a minimum of upheaval and consequently rapid, defect-free and economical processes. These goals can be attained and guaranteed in the planning departments of businesses through the sharing of secure and up-to-date planning data, leading to a high degree of flexibility and a minimum of interruptions in the production processes. In terms of technology planning, this results in a demand for economic methods of planning and NC programming, leading in turn to continuous, systematic acquisition of specialised in-house technological knowledge. However, most of the applications on the market are unsatisfactory in terms of acquisition of specialised knowledge of technology, only allowing specialised planning knowledge to be gathered or entered through costly procedures and for it to be organised statically. For rational processing and evaluation of planning knowledge, it is therefore sensible to systematically record technological discoveries made in the course of the planning and running-in process and to make them available for future planning processes. This processing of empirical knowledge along with rational and safe technology planning is supported by the use of DP systems, thus enabling planning knowledge to be kept constantly up-to-date, growing along with the data specific to the enterprise. For this purpose, a suitable information model must be devised that represents the integration point within the NC process chain. Using a feature-based product model introduced in the design departments as a starting point, the model is extended to take in a production-orientated view. The model should be designed in such a way that, above all, the technological interconnections are represented and that the technology planning, NC programming and running-in process are integrated through the model. In order to evaluate and process empirical knowledge, methods are applied from machine learning from Bayesian belief networks. This enables a costly human acquisition of the empirical knowledge of technology to be avoided and a rapid and rational decision-support system tailored to the particular problem to be developed. Also, by using suitable Bayesian belief networks, planning knowledge can be condensed, the numerous different planning conditions can be automatically diverted and the decision-base kept extremely up-to-date.

Optimal cutter selection and machining plane determination for process planning and NC machining of complex surfaces

Abstract This paper deals with the optimal cutter selection and machining plane determination problems for NC machining and process planning. Two optimization methods, an integer programming (IP) method and a dynamic programming (DP) method, are presented. While the IP method provides an upper bound for such a problem, the DP method provides an optimal solution at the cost of longer computational time. Both methods can be used to automate the traditional, experience-based cutter selection tasks and to reduce the total machining time in NC machining operations. Numerical examples are included to illustrate both methods.

A multipass optimization strategy for CNC lathe operations

The optimization of cutting conditions has been and still is an active area of research since Gilbert's (1950) first work in machining economics. Many concepts and optimization procedures have been developed since then to obtain optimum conditions, taking into account as many influencing variables as possible. However, the use of these techniques in machinability data base systems, NC part programming systems and process planning systems so far has been very limited, even though there is an urgent need for such a technique. Existing optimization schemes do not necessarily give optimum machining solutions. Several works reported in the literature restricted multi-pass problems to two-pass problem so as to simplify the solution method or to treat them as single-pass problems. This paper describes the development of a methodology for an effective optimization of machining conditions of multi-pass lathe operations. The objective is to use the optimal even depth of cut strategy to simplify the solution method that determines near-optimum and practical solutions. The solutions obtained can be conveniently implemented in the part programmes of a CNC lathe. Such work can provide a wider acceptance and more practical application of machining economics in industry.

CARDAM—an integrated design and manufacturing system for roll forming tools

This article deals with the development of an integrated design and manufacturing system (CARDAM) for roll forming tooling. The roll forming process has been organised into three distinct modules: roll form design, roll profile editing and NC processing of roll profiles. The roll design module automatically generates section drawing, flower pattern, mill parameters, and roll drawings to design specifications. The roll editing module generates the roll profile geometry data essential for the NC processor. This provides the link for integrating CAD and CAM facilities. The NC processor uses roll profile data as input geometry and finally generates NC codes for the roll machining process. This article brings out the facilities incorporated into the CARDAM system through a design example.