Computer application for decisionmaking support in metal spinning.
Forming is a manufacturing process, which plays the dominant role in the nowadays competitive industry. Most of the existing forming processes are feasible for large batches. On the other hand, the diversified customer's demands have created a recent trend towards the small-batch production. One of the relatively old, but now high-tech computerized forming technology, which offers attractive cost benefits and is appropriated for production of one-offs and prototypes as well as to medium runs and, for certain part applications, high-volume manufacturing, is metal spinning. It is technology, which produces axially symmetric hollow light-weight sheet parts with advantageous surface layer properties.
There are three types of metal spinning techniques. The first process, in which the thickness of workpiece is almost unchanged, is called conventional or multipass spinning. In conventional spinning, it is assumed that the sheet thickness is constant and the hoop strain is compressive, the radial strain is tensile and the thickness strain is zero. The second process, where the hoop strain is zero, is named pure shear forming, also named power spinning (Bewlay & Furrer, 2006) or spin forging (Quigley &Monaghan, 2000). In shear forming the radial position of any element is unchanged and a single pass is usually all that is required to produce the desired shape (Razavi, 2005). The third metal spinning technique is named tube spinning or flow forming. In this method the heated end of the tube blank, rotating with a certain angular velocity, is deformed by the friction tool.
Metal spinning fundamentals are simple. A round blank, flat or preformed, is fixed in a spinning lathe. As the blank spins, a rigid or roller tool forms it, usually pressing the blanks against the mandrel.
The principle of the conventional metal spinning process shows Fig. 1.
[FIGURE 1 OMITTED]
Spinning, compared with deep drawing, involves lower forming forces and less power. As a result, equipment is cost-effective engineered and process is very flexible. Other benefits are: increased level of automation, high mechanical strength and hardness of part material, very low risk of crack propagation, cost reduction through high material yield and a favorable cycle time. These benefits apply to production of one-offs and prototypes as well as to small to medium runs. Nowadays the process is getting increasing importance in many fields of industrial applications. The process can produce a wide variety of shapes, providing unlimited opportunities for part designers as well as for new applications. The range of components include gas centrifuges, funnels, tanks, bottles, cooking pots and pans and many other components for automobile, defence, aerospace, agricultural industries. It also has the possibility of producing parts that could not be deep drawn (Palten & Palten, 2002).
A lubricant is almost always used during power spinning. The fluid used serves as both a lubricant and a coolant. A water-based coolant, such as an emulsion of soluble oil in water, is most commonly used, and in large quantities because of the large amount of heat generated. When spinning aluminium, stainless steel, or titanium, the workpieces or mandrels or both are sometimes coated with the lubricant before spinning. An increase in the forming temperature can lead to a reduction in the flow stress and an increase in the ductility of the preform; this is sometimes required if the load capacity of the spinning machine is not sufficient for cold forming of the preform or if the room-temperature ductility of the work metal is too low. When operating at elevated temperatures, great diligence must be exercised in the selection and use of an appropriate lubricant (Bewlay & Furrer, 2006).
In spinning process, proper selection of tool and lubricant is not important only for successful forming of the sheet metal components, but also equally affects the surface quality of spun part. But the selection of the appropriate lubricant is still more an art than a science, because there is no standardized method available for this purpose.
The traditional selection of lubricant is mostly based on type of metal spinning operation, material being spun, spinning tool material and spinning conditions - mandrel frequency of rotation and tool feed. Innovative methodologies for decision support in the forming lubricant selection process must consider the environmental, health and safety characteristics, too.
The main human risks generated by forming lubricant application are dermatological risk, inhalation risk and toxicity action. It can be also harmful for the environment. While some of these characteristics are available from Material Safety Data Sheet (MSDS), this information is far from comprehensive and also is often only qualitative. Once a data base of lubricants and their characteristics have been established, decision makers are still left with a problem: what is the difference between two lubricants. Database of lubricants and their properties is not enough. A method to group these media into categories on the base of similarity of their properties is also needed.
The development of computer application called LUHAS "Lubricant Health Assessment System", designed for the optimization of the lubricants selection with regard to human and environmental risks, is presented in this contribution.
2. Computer application for decision-making support in metal spinning
The experimental investigation focused on the metal spinning process parameters optimization is realized at the Department of Manufacturing Technology and Material Science, Faculty of Environmental and Manufacturing Technology, Technical University in Zvolen. The main interest of the research is put on the analysis of strain distribution through the formed part after metal spinning operations (Sugar & Sugarova, 2002), study of microstructure and formed part wall thickness changes after metal spinning (Gasparova, Sugarova & Kalincova, 2006) and the shape accuracy analysis of spun parts (Sugar, Sugarova & Morovic, 2008).
One part of the research is creation of computer application for decision-making support in the stage of metal spinning process design. One module of the system brings the ability to compare the toxicological and ecotoxicological parameters of the lubricants used in the metal spinning process.
2.1 Forming lubricants attributes
The forming lubricants attributes are defined by these properties or characteristics: viscosity, film formation, cooling capacity, stability, thermal conductivity, antifoaming characteristics, toxicity, flammability, treatment and so on. Consideration of forming lubricants for "green manufacturing" includes the environmental, health and safety impact. Some of these values are expressed by the risk phrases.
Risk phrases (R-phrases) are used as a method of labelling commercial substances after they have been classified toxicologically by the possible hazards to humans resulting from their use. R-phrases are defined in Annex III of European Union Directive 67/548/EEC. R-phrase definitions cover most health effects resulting from exposure via ingestion, skin contact and inhalation.
2.2 System requirements and installation
The computer application LUHAS is designed to run in Windows 2000/XP/Vista, so the minimum hardware requirements are determined by these operating systems. In addition, it has to be installed Microsoft .NET Framework 2.0 and DAO 3.7+. Minimum hardware requirements are: processor Intel Pentium III 500 MHz, 128 MB RAM, 20 GB HDD. The "LUHAS" can be installed by following the installation steps in Setup.exe.
2.3 Structure of the system
The principal structure of the application has been created by these three modules (Fig. 2.):
* database module,
* user interface module,
* process optimization module.
[FIGURE 2 OMITTED]
2.4 Database module
Data included in sections of MSDS (Material Safety Data Sheet) will serve as input data for the development of a lubricant database with toxicological information created using Microsoft Access.
Structure of the database is given by these tables:
* identification of manufacturer--name and location of company,
* identification of product/lubricant--name,
* identification of health risks--health hazard symbols and R-phrases,
* toxicological information (acute toxicity--oral, dermal, inhalation; subacute (subchronic) toxicity; chronic toxicity--mutagenicity, carcinogenicity, toxicity for reproduction),
* identification of environmental risks--environmental hazard symbol and Rphrases,
* ecotoxicological information (aquatic toxicity, biodegradability, bioaccumulation).
The database includes several tables, which are interconnected--into a relational database. It is important to specify the relationships between individual tables (see Fig. 3.):
* one manufacturer may have more products (lubricants),
* some product can have more health hazard symbols, R-phrases and toxicological information,
* toxicological and ecotoxicological information can vary by products,
* health hazard symbol can have more R-phrases,
* R-phrase can be used by more health hazard symbols.
[FIGURE 3 OMITTED]
2.5 User interface module
The user interface module is user-friendly and is made by the form of windows. It is designed to control the operation of the whole application, for data input, editing and deleting as well as for reporting the results. The user can log into the application by entering the user name and password (Fig. 4.).
[FIGURE 4 OMITTED]
After login in, the Main Form of the application appears (Fig. 5.). It has the main menu with File, Search and Help and secondary menu with Edit, Add New and Delete. The user can view the list of lubricants, manufacturers, symbols, R-phrases and toxicological information by choosing Search. The data can be edited by clicking Edit or deleted by choosing Delete. Saving of data is automatic and changes automatically appear in database. The information about a lubricant can be printed by choosing File and then Print at any time.
The application can be extended in further development and new data may be added by choosing Add New in Main Form. After that, Data Input Form appears (see Fig. 6). The user can add here the name of a lubricant, its manufacturer, the health and environmental hazard symbols (degree, abbreviation and description), R-phrases and eco/toxicological information of a lubricant (e.g. toxic in contact with skin, irritant to eyes, harmful to aquatic organisms, etc.). Saving of the added data is automatic.
[FIGURE 5 OMITTED]
[FIGURE 6 OMITTED]
2.6 Process optimization module
The process optimization module is the main part of the application. It includes the comparison and health and environmental assessment of lubricants. The user can launch this module by choosing File and then Lubricants health assessment. The model of this assessment is based on the similarity comparison.
[FIGURE 7 OMITTED]
The principle is to compare the health and environmental properties of a given lubricant, which are represented by R-phrases, with the health / environmental properties of a reference lubricant. The reference lubricant has maximum number of R-phrases and represents the worst health variant.
Similarity is defined in terms of a distance metric, most often Euclid distance ([d.sub.E]) or relatives of the Euclid distance. The similarity index between the lubricants is defined as follows:
[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (1)
[g.sub.i] is the weighting factor of the i-th lubricant property, [x.sub.i], [y.sub.i] are values of the i-th lubricant property.
Some of the weighting factors for individual properties are shown in Tab. 1. The basis for the weights allocation of each R--phrase or their combination takes into account the seriousness of the resultant health/environmental effects.
The weights are numbered from 1 to 10. The acute toxicity--oral, dermal, inhalational, describes the adverse effects of a substance which result either from a single exposure or from multiple exposures in a short space of time (usually less than 24 hours). It is less harmful and is ranked with a lower degree. Chronic toxicity is a property of a substance that has toxic effects on a living organism, when that organism is exposed to the substance continuously or repeatedly. The chronic toxicity as mutagenicity, carcinogenicity and toxicity for reproduction are more dangerous for the health of people, therefore are ranked with high numbers.
The Euclid distance indicates how much the given lubricant is similar to the reference one. The bigger the index is, the more different the lubricants are and the less harmful a lubricant to the health of workforce and environment is. If [d.sub.E] equals zero, it means that the lubricants are identical. It is the worst variant.
The ultimate objective of process planning is to obtain robust decisions in processes, parameters, and catalyst selection through a multi-objective optimization algorithm (Srinivasan & Sheng, 1999). Computer-aided process planning systems have been devised to help simplify, improve, and provide consistency within the process planning function. one of the many process planning tasks in metal spinning is selection of optimal lubricant. lubricants have a number of attributes by which they may be judged as selection candidates.
The problem of choosing the most suitable lubricant from among a group of lubricants which may be better in some respects but worse in others is multi-attribute decision problem. It is obvious that the selection of the appropriate lubricant has to be governed not only with functional requirements and cost performance but as well health hazards and environmental performance.
This paper has introduced software tool for lubricants evaluation based on health and environmental risks. The tool enables the calculation of overall score to measure health/environmental performance of a given lubricant. possible utilisation of developed tool includes predictive assessment of health/environmental impacts of lubricant in metal spinning process planning and valuable instrument in education process. There is a need for teaching students in fundamental cApp principles and in solving real world problems using computers. The industrial praxis demands engineering graduates that understand tasks of manufacturing process planning and are health and environmentally-conscious.
Further research needs to be undertaken to determine the system errors. The software design presented here is a first approach to understand the health and environmental decisions to be made to choose the most harmless lubricant from the list of potential lubricants appropriate for their use in a given operation. The last task will be the implementation of developed software as a separate module into some existing CAPP systems. This has to be continued and further tested in practical tasks of metal spinning applications.
The authors wish to thank the financial support of the Ministry of Education of the Slovak Republic, in framework research project VEGA No. 1/4097/07: "Expert systems for technological parameters optimization in metal spinning processes" and MANUNET project Met-Spin.
Bewlay, B. P. & Furrer, D. U. (2006). Spinning, Available from: http://www.asminternational.org Accessed: 2009-04-20
Gasparova, J.; Sugarova, J. & Kalincova, D. (2006). Study of microstructure and formed part wall thickness changes after metal spinning, In: Development of Mechanical Engineering as a Tool for Enterprise Logistic Progress, Legutko, S., (Ed.), pp. 187-192, ZPW M-DRUK, ISBN 83-89873-28-1, Poznan
Palten H. & Palten, D. (2002). Metal spinning--From Ancient Art to High-Tech Industry, Available from: http://archive.metalformingmagazine.com/2002/09/ MetalSpin.pdf Accessed: 2009-04-20
Quigley, E. & Monaghan, J. (2000). Metal forming: an analysis of spinning processes. Journal of Materials Processing Technology, Vol. 103, No.1, pp. 114-119, ISSN 0924-0136
Razavi, H.; Biglari, F. R. & Torabkhani, A. (2005). Study of Strains Distribution in Spinning Process Using FE Simulation and Experimental Work. Available from: http://me.aut.ac.ir/frbiglari.htm Accessed: 2008-06-24
Srinivasan, M. & Sheng, P. (1999). Feature-based process planning for environmentally conscious machining--Part 1: microplanning. Robotics and Computer Integrated Manufacturing, Vol. 15, No. 3, (June 1999), pp. 257- 270, ISSN 0736-5845
Sugarova, J. & Sugar, P. (2002). Research study of strain distribution throughout the part after metal spinning operations. In: Annals of DAAAM for 2002 & Proceedings of the 13th International DAAAM Symposium, Katalinic, B., (Ed.), pp. 545-546, DAAAM International, ISBN 3-901509-29-1, Vienna
Sugarova, J., Sugar, P. & Morovic, L. (2008). Application of 3D optical scanning for the shape accuracy analisis of machine parts produced by multi-pass metal spinning. In: Annals of DAAAM for 2008 & Proceedings of the 19th International DAAAM Symposium, Katalinic, B., (Ed.), pp. 1331-1332, DAAAM International, ISBN 3-901509-29-1, Vienna
This Publication has to be referred as: Meciarova, J[ulia]; Dado, M[iroslav]; Sugar, P[eter] & Sugarova, J[ana] (2009). Computer Application for DecisionMaking Support in Metal Spinning, Chapter 34 in DAAAM International Scientific Book 2009, pp. 323-332, B. Katalinic (Ed.), Published by DAAAM International, ISBN 978-3-901509-69-8, ISSN 1726-9687, Vienna, Austria
Authors' data: PhD. MSc. Meciarova, J[ulia] *; PhD. MSc. Dado, M[iroslav] *; Assoc. Prof. PhD. MSc. Sugar, P[eter] **; PhD. MSc. Sugarova, J[ana] **, * Technical University in Zvolen, Studentska 26, 960 53, Zvolen, Slovak Republic, ** Slovak University of Technology in Trnava, J. Bottu 23, 917 24, Trnava, Slovak Republic, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com
Tab. 1. Some of the weighting factors for individual health/environmental effects R-phrase Weight R48/20/21/22 8,3 R48/23, R48/24, R48/25 8,4 R48/23/24, R48/23/25, R48/24/25 8,5 R48/23/24/25 8,6 R39, R40, R45, R62, R63, R64 9 R39/23, R39/24, R39/25 9,1 R39/23/24, R39/23/25, R39/24/25 9,2 R39/23/24/25 9,3 R39/26, R39/27, R39/28 9,4 R39/26/27, R39/26/28, R39/27/28 9,5 R39/26/27/28 9,6 R46, R49, R60, R61 10
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|Title Annotation:||Chapter 34|
|Author:||Meciarova, J.; Dado, M.; Sugar, P.; Sugarova, J.|
|Publication:||DAAAM International Scientific Book|
|Date:||Jan 1, 2009|
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