- Email: [email protected]
CCKBS: A component check knowledge-based system for assessing manufacturability of sheet metal parts
Journal of Materials Processing Technology 172 (2006) 64–69
CCKBS: A component check knowledge-based system for assessing manufacturability of sheet metal parts Shailendra Kumar a,∗ , Rajender Singh b , G.S. Sekhon c a b
Department of Mechanical Engineering, HCE, Sonepat, Haryana, India Department of Mechanical Engineering, CRSCE, Murthal, Haryana, India c Department of Applied Mechanics, IIT, New Delhi 110016, India
Received 3 September 2004; received in revised form 17 August 2005; accepted 3 September 2005
Abstract This paper describes a knowledge-based system developed for assisting product designers, process planners and die designers working in small and medium sheet metal industries for assessing manufacturability of sheet metal parts. Knowledge obtained from die designers, product design handbooks, catalogues and broachers has been analyzed, tabulated and incorporated into a set of production rules of the IF–THEN variety. The knowledge-based system is coded in the AutoLISP language and loaded into the prompt area of AutoCAD. During consultation, the proposed system generates friendly prompt eliciting from the user for job related. The system output includes recommendations on the suitability of geometrical features of the part for required manufacturing operations. This arrangement facilitates interfacing of design with drafting and can be operated on a PC/AT. Illustrative examples have been included for demonstrating the usefulness of the proposed system. The knowledge base of the proposed system can be modified depending upon the capabilities of a specific shop floor. The low-cost of the system makes it affordable for planners working in small and medium-sized enterprises. © 2005 Elsevier B.V. All rights reserved. Keywords: Knowledge-based system; Manufacturability; Sheet metal parts; Knowledge base
1. Introduction From manufacturability point of view, correct selection and placement of design features on a part, remains even today more of an art than a science [1]. This is on account of the fact that the die designer is called upon to effect trade-offs between a numbers of mutually conflicting factors at initial stages of design. Indeed many practitioners in industry believe that the art of part, process and die design can be mastered only through long years of experience [2]. Traditional methods of checking manufacturability of the part involve numerous calculations and decisions, which have to be made on the basis of experience and practice codes without the computer aids. Also, the product designer, process planner and die designer may have to spend many hours consulting handbooks, going through empirical formulae, perusing tabulated and graphical information, and making ∗ Corresponding author at: Department of Mechanical Engineering, Hindu College of Engineering, Industrial Area, Sonepat, 131001 Haryana, India. Tel.: +91 130 2210756; fax: +91 130 2210755. E-mail address: [email protected] (S. Kumar).
0924-0136/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jmatprotec.2005.09.001
calculations before arriving at workable designs. Beside this, the manual method of testing manufacturability of the part is tedious and time consuming, and often does not yield optimum results. There exists therefore, the need of developing low-cost knowledge-based systems [3] that are capable of providing intelligent advice to the planners of sheet metal operations especially one employed in the small-scale industry. In recent years the computer-aided procedures [4–8] are being increasingly utilised to ameliorate the above difficulties. The specific objectives of the present work is the development of a knowledge-based system for assisting the product designers, process planners and die designers to check the correctness of the geometrical features of the part on manufacturability basis. The AutoLISP language has been utilised in the proposed knowledge-based system, since it can be interfaced with AutoCAD for computer-assisted drafting, designing and manufacturing of die components for sheet metal operations. For consultation, the user loads the knowledgebased system into the prompt area of AutoCAD. The proposed system generates friendly prompt eliciting from the user for data pertaining to the job at hand. The system output includes recommendations on suitability of geometrical features of the part for
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
required manufacturing operations. The system is flexible and its knowledge base can be extended and modified as old manufacturing facilities are discarded or newer ones are acquired in a particular enterprise. 2. Considerations for checking manufacturability of the part As a first step in the planning of manufacture of a sheet metal component, it is useful to check whether certain of its design features are conducive to ease of manufacture. Such checks are useful to avoid manufacturing defects, section weakness, and need of new dies, tools or machines. Dimensions and location of internal and external features such as holes, extended holes, internal contours, external contours, cuts, notches, bosses, cups, slots and bends should be tested against rules of good practice. One should consider the following information while checking manufacturability of the part: (a) The corner radius on sheet metal parts should be at least 0.7 times of sheet thickness. (b) The width of recesses or slots or projections along blank profile should be minimum 1.2 mm. (c) The permissible minimum diameter of piercing depends on the type of sheet material, shape of holes and sheet thickness. For piercing round holes, the diameter should not be less than 0.5 mm for hard steel sheet material and 0.4 mm for soft steel, brass or aluminium sheet material. The size of a square or rectangular hole should not be less than 0.35 mm for soft steel, brass or aluminium sheet material. (d) The spacing between holes on sheet metal parts should be at least 2.0 times of sheet thickness. 3. Development of the knowledge-based system The procedural steps [9] in the development of the proposed knowledge-based system (KBS) involve selection of knowledge representing language, Collection of information on manufacturability, preparation of knowledge base and development of user friendliness. A brief description of each step is given below. 3.1. Selection of knowledge representing language Early expert systems were written in language interfaces derived from FORTRAN. Later on, object-oriented languages such as KEE, OPS, PROLOG, TURBO, PROLOG and LISP were developed specifically for the knowledge-based systems [10]. LISP and PROLOG have won wide acceptance for building such intelligent systems [11]. But the user of these languages encounters difficulties when handling design problems involving graphical information. For this reason, AutoCAD [12,13] and AutoLISP [14,15] have found greater acceptance in design and manufacturing, evaluation of design alternatives, and creation of drawings. Expert system applications involving graphical data can be built by combining AutoLISP and AutoCAD [16]. For this reason, the present system makes use of AutoLISP and AutoCAD facilities.
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3.2. Collection of information to check manufacturability Information to check manufacturability are essentially collection of bits and pieces of published, or unpublished, analytical or empirical knowledge from a variety of sources including experienced product designers, process planners and die designers, shop floor engineers, and handbooks, monographs, research journals and industrial brochures. The chief data sources utilised during the present investigation are listed in References [17–25]. Information on manufacturability checks was culled from industrial experts by holding discussions on typical problems and letting the experts talk about the approach, formulae and thumbrule relied upon by them. They were asked as to how and why a particular decision was reached. This was done to identify the parameters influencing the manufacturability of the part for a particular decision. The data, facts and judgment obtained from each expert were recorded, transcribed and then checked with other experts before formalising into production rules. The experts were also observed while working. Design recommendations contained in the “manufacturability manual” of the company can also be incorporated in the form of production rules. 3.3. Preparation of knowledge base The common systems of creating a knowledge base are through either production rules or frames [26]. The production rule-based system is the earlier and more popular approach to represent analytical, heuristic or experience based knowledge. The production rules are usually of the IF (action)–THEN (conclusion) kind. The frame based knowledge representation scheme uses a hierarchy of frames where each single frame is a template that holds a unit of data, fact, rule or hypothesis. The knowledge base of the proposed system is based on production rules. The production rules are carefully structured by considering both the domain knowledge as well as shop specific information. These rules may be arranged either in an unstructured (arbitrary) or a structured manner. In the latter case, the rules tend to be simpler and briefer because they are designed to “fire” in some hierarchical manner. The sequencing of rules of the proposed KBS is unstructured. The production rules have been encoded with the help of AutoLISP language. This arrangement allows insertion of new production rules even by relatively less trained knowledge engineers. For searching a solution to a particular problem, two strategies called as the forward chaining and backward chaining are generally used [27]. In forward chaining, the user interactively supplies system data or facts about the problem to be solved. The system searches the IF conditional data to determine which rules are satisfied by the given facts. Whenever a particular IF condition is found to have been satisfied, the THEN portion of the rule is gets activated leading to a conclusion or an advice. The search is continued till the complete solution is found. On the other hand, in backward chaining, the search proceeds ahead or moves backward to support a hypothesis or a goal. The proposed production rule-based KBS makes use of forward chaining. A sample of the production rules incorporated in the present KBS is given in Table 1.
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Table 1 A sample of production rules included in the proposed knowledge base system IF
THEN
1 2 3 4 5
Minimum corner radius in mm ≥0.7 times sheet thickness Minimum corner radius in mm <0.7 times sheet thickness Width of recesses or slots or projections along blank profile ≥1.2 mm Width of recesses or slots or projections along blank profile <1.2 mm Sheet material = ‘Hard Steel’ and shape of hole = round and 0.5 mm ≤minimum hole diameter ≥1.3 times of sheet thickness Sheet material = ‘Hard Steel’ and shape of hole = round and minimum round hole diameter <0.5 mm Sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ shape of hole = round and 0.4 mm ≤minimum round hole diameter ≥sheet thickness sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ and shape of hole = round and minimum round hole diameter <0.4 mm Sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ and shape of hole = square or rectangular and 0.35 ≤minimum dimension of hole ≥0.7 times of sheet thickness Sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ and shape of hole = square or rectangular and minimum dimension of hole <0.35 mm Minimum hole pitch ≥2.0 times sheet thickness Minimum hole pitch <2.0 times sheet thickness Minimum bend corner radius in mm ≥3.0 times sheet thickness and 2
“Accept the corner radius” “Set minimum corner radius = 0.7 times sheet thickness” “Accept width of recesses or slots or projections” “Set width of recesses or slots or projections = 1.2 mm” “Accept the diameter of hole”
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
“Set minimum diameter of hole = 0.5 mm” “Accept the diameter of hole” “Set minimum diameter of hole = 0.4 mm” “Accept the dimension of hole” “Set the minimum dimension of hole = 0.35 mm” “Accept hole pitch” “Set minimum hole pitch = 2.0 times sheet thickness” “Accept the bend corner radius” “Set minimum bend corner radius on part = 3.0 times sheet thickness” “Set minimum bend corner radius on part = 2.5 times sheet thickness” “Set minimum bend corner radius on part = 1.5 times sheet thickness” “Set lead end scrap web allowance in mm = 1.25 times sheet thickness” “Set minimum lead end scrap web allowance = 1.5 mm” “Set minimum front/back scrap web allowance = 1.5 mm” “Set lead end scrap web allowance in mm = 1.75 times sheet thickness” “Set front/back scrap web allowance in mm = 1.75 times sheet thickness”
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
S. No.
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
3.4. Development of user friendliness The purpose of development of user friendliness is two-fold. It enables the user input the essential the job related data to the system and it displays the intelligent advice for the user’s benefit. This is achieved by making the interface flash prompts at appropriate stages during a consultation inviting the user input data items. It also displays messages or items or advice on the computer screen at appropriate times. The user is guided in a friendly manner throughout the consultation on how to proceed further at each different stage. 4. Description of the proposed knowledge-based system Heuristic knowledge for the construction of the proposed KBS was obtained from various sources as discussed earlier. Examples of the production rules based on the knowledge so
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acquired are given in Table 1. These rules were encoded in AutoLISP. The system incorporates an interface for displaying friendly prompts to guide the user during a consultation session. The chief purpose of the prompts is to ask the user to input the needed data. The user initially loads the program by using the command (LOAD “A: PARTDGN.LSP”) in prompt area of AutoCAD. The program, after compilation, is ready for serving the user. As soon as the user has supplied sufficient data during a consultation, the program scans through the production rules one after the other. Whenever the IF condition in a production rule gets satisfied, the module displays the THEN advice for benefit of the user. The proposed KBS described above was tested by considering the problem of checking manufacturability of the part for the two real industrial components shown in Figs. 1 and 2. Typical prompts, user responses and the recommendations obtained by the user during the execution of the program for the example problems are given through
Fig. 1. Example component 1 (dimension: mm, sheet material: brass, sheet thickness: 0.6 mm).
Fig. 2. Example component 2 (dimensions: mm, sheet material: brass, sheet thickness: 3.0 mm).
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
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Table 2 Typical prompts, user responses and expert advice during execution of the proposed knowledge base system for example component 1 S. No. 1 2 3 4 5 6 7 8 9 10
Prompt
Example data entry
Advice to the user
Please enter sheet material Please enter sheet thickness in mm Please enter the minimum corner radius sheet metal part in mm Please enter minimum width of recesses or slots or projections along blank profile in mm Please enter shape of holes on the part Please enter minimum dimension of round hole on part in mm. Please enter minimum dimension of rectangular hole on part in mm Please enter minimum hole pitch in mm. Please enter the shape of component edge Please enter the maximum dimension of the component in mm (length/width)
Brass 0.6 0.001 1.6
“Set minimum corner radius on part in mm = 0.42” “Accept width of recesses or slots or projections”
Round and rectangular 2.5 5.2 6.1 Straight 62.0
“Accept the dimension of hole” “Accept the dimension of hole” “Accept hole pitch” “Set lead end scrap web allowance in mm = 1.5” “Set front/back scrap web allowance in mm = 1.5”
Table 3 Typical prompts, user responses and expert advice during execution of the proposed knowledge base system for example component 2 S. No.
Prompt
Example data entry
1 2 3 4
Please enter sheet material Please enter sheet thickness in mm Please enter the minimum corner radius on sheet metal part in mm Please enter minimum width of recesses or slots or projections along blank profile in mm Please enter shape of holes on the part Please enter the minimum diameter of round hole on part in mm. Please enter minimum hole pitch in mm. Please enter the shape of component edge Please enter the maximum dimension of the component in mm (length/width)
Brass 3.0 1.75
5 6 7 8 9
Tables 2 and 3. The recommendations obtained were found to be reasonable and very similar to those actually used in industry (Indo-Asian Fuse Gear Ltd., Murthal, Haryana, India for the component shown in Fig. 1 and Anurena Tristar Ltd., Delhi, India for the component shown in Fig. 2). Notable features of the proposed system are its lowest cost and the linking of the die design process with quick drafting of die assembly and die components. The knowledge base of the system can be easily modified or expanded by changing in the existing production rules or adding new rules. Additional modules can also be added to meet the changing requirements of the production unit.
Round 5.0 14.20 Straight 245.27
Advice to the user
“Set minimum corner radius on part in mm = 2.1” Not applicable
“Accept the diameter of holes” “Accept hole pitch” “Set lead end scrap web allowance in mm = 5.25” “Set front/back scrap web allowance in mm = 5.25”
ple dies, compound dies, progressive dies and combination dies for carrying out operations such as piercing, blanking, notching, forming, cropping, shearing, trimming, clipping, parting, slitting, perforating, bending and drawing. Illustrative examples have been included for demonstrating the usefulness of the proposed system. The knowledge base of the proposed system can be modified depending upon the capabilities of a specific shop floor. The low-cost of the system makes it affordable for planners working in small and medium-sized enterprises.
References 5. Conclusion Knowledge for checking manufacturability of sheet metal part, obtained from product designers, process planners, die designers, handbooks, catalogues, and brochures has been analyzed, tabulated and incorporated into a set of production rules. The procedure used for constructing the knowledge base system is explained at some length. The proposed knowledge base system has been designed as a low-cost alternative for use in by sheet metal planners and is capable of checking manufacturability of the part for sheet metal operations. Application of the proposed system is illustrated through examples. The system imparts intelligent advice to the user on product manufacturability point of view at the initial stages of die design. The proposed system applies to situations involving the use of sim-
[1] F. Strasser, Functional Design of Metal Stampings, Society of Manufacturing Engineers, Dearborn Michigan, 1971. [2] S.K. Sitaraman, G.L. Kinzel, T. Altan, A knowledge base system for process–sequence design in axi-symmetric sheet metal forming, J. Mater. Process. Technol. 25 (1991) 247–271. [3] B.T. Cheok, A.Y.C. Nee, Trends and developments in the automation of design and manufacture of tools for metal stampings, J. Mater. Process. Technol. 75 (1998) 240–252. [4] B.T. Cheok, K.Y. Foong, A.Y.C. Nee, An intelligent planning aid for design of progressive dies, Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 210 (1996) 25–35. [5] R. Singh, G.S. Sekhon, A low cost modeller for optimal stamping layouts for sheet metal operations, in: Proceedings of the International Conference, Belgium, 2–4 April, 2001, pp. 363–370. [6] R. Singh, G.S. Sekhon, An intelligent system for optimal selection of dies and tools for sheet metal operations, Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 216 (2002) 821–828.
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69 [7] J.Y. Li, A.Y.C. Nee, B.T. Cheok, Integrated feature-based modelling and process planning of bending operations in progressive die design, Int. J. Adv. Manuf. Technol. 20 (2002) 883–895. [8] R. Singh, G.S. Sekhon, Design and application of hybrid software for modelling die components and die assembly, Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf. 217 (2003) 235–250. [9] S. Kumar, R. Singh, A low cost knowledge-based system framework for progressive die design, in: Proceedings of the International Advances in Materials and Processing Technologies (AMPT-2003) Conference, Dublin, 8–11 July, 2003, pp. 1614–1617. [10] A. Barr, E.A. Feigenbaum, The Handbook of Artificial Intelligence, vol. 1, William Kauf Manu, Loss Altos, CA, 1981. [11] B.R. Gaines, Rapid prototyping for expert system, in: Michael Dliff (ed.), Intelligent Manufacturing, l988, pp. 45–73. [12] L.R. Danial, Computer Aided Design for AutoCAD Users, Prentice Hall, Englewood Cliffs, NJ, 1989. [13] R. Gary, Berto Line AutoCAD for Engineering Graphics, Collier MacMillan Publishers, London, 1990. [14] O.H. George, AutoLISP in Plain English, Venlana Press, Chapel Hill, North Carolina, 1987. [15] Thomas M. Robert, Advanced Techniques in AutoCAD, Business Promotion Bureau Publications, New Delhi, 1988. [16] D. Jain, L.M. Marry, Combining expert system and CAD techniques, in: Artificial Intelligence Developments and Application, Elsevier Science Publishers, 1988.
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[17] F.D. Jones, Die Design and Die Making Practice, The Industrial Press, New York, 1941. [18] C.W. Hinman, Press Working of Metals, McGraw-Hill, New York, 1950. [19] D.F. Ostergard, Advanced Die Making, McGraw-Hill, New York, 1967. [20] F. Strasser, Functional Design of Metal Stampings, Society of Manufacturing Engineers, Dearborn, Michigan, 1971. [21] K.A. Keyes, Press Working Stamping and Dies, Society of Manufacturing Engineers, Dearborn, Michigan, 1982. [22] J.R. Paquin, R.E. Crowley, Die Design Fundamentals, Ind. Press Inc., New York, 1987. [23] D.A. Smith, Die Design Handbook, Society of Manufacturing Engineers, Dearborn, Michigan, 1990. [24] R. Prasad et al., Tool design parameters, Technical Report, Indian Telephone Industries Ltd., Banglore. [25] Industrial experts, S.L. Gupta, DGM (Mindarika Pvt. Ltd., Gurgaon, India), Manohar Lal, DGM (Prod.) and P.V. Mohan Rao, Manager (Tool Design), TRTC, Wazir Pur, Delhi, India and Dr. B.K. Khan, Principal, B.R.C.M. College of Engineering, Haryana, India. [26] P. Kinnucan, Computers That Think Like Experts, High Technology, 1984. [27] B.G. Bachanan, E.H. Stohlafte, Rule-based Expert System, Addisor Willey Publishing Company Inc., Reading, MA, 1984.
CCKBS: A component check knowledge-based system for assessing manufacturability of sheet metal parts Shailendra Kumar a,∗ , Rajender Singh b , G.S. Sekhon c a b
Department of Mechanical Engineering, HCE, Sonepat, Haryana, India Department of Mechanical Engineering, CRSCE, Murthal, Haryana, India c Department of Applied Mechanics, IIT, New Delhi 110016, India
Received 3 September 2004; received in revised form 17 August 2005; accepted 3 September 2005
Abstract This paper describes a knowledge-based system developed for assisting product designers, process planners and die designers working in small and medium sheet metal industries for assessing manufacturability of sheet metal parts. Knowledge obtained from die designers, product design handbooks, catalogues and broachers has been analyzed, tabulated and incorporated into a set of production rules of the IF–THEN variety. The knowledge-based system is coded in the AutoLISP language and loaded into the prompt area of AutoCAD. During consultation, the proposed system generates friendly prompt eliciting from the user for job related. The system output includes recommendations on the suitability of geometrical features of the part for required manufacturing operations. This arrangement facilitates interfacing of design with drafting and can be operated on a PC/AT. Illustrative examples have been included for demonstrating the usefulness of the proposed system. The knowledge base of the proposed system can be modified depending upon the capabilities of a specific shop floor. The low-cost of the system makes it affordable for planners working in small and medium-sized enterprises. © 2005 Elsevier B.V. All rights reserved. Keywords: Knowledge-based system; Manufacturability; Sheet metal parts; Knowledge base
1. Introduction From manufacturability point of view, correct selection and placement of design features on a part, remains even today more of an art than a science [1]. This is on account of the fact that the die designer is called upon to effect trade-offs between a numbers of mutually conflicting factors at initial stages of design. Indeed many practitioners in industry believe that the art of part, process and die design can be mastered only through long years of experience [2]. Traditional methods of checking manufacturability of the part involve numerous calculations and decisions, which have to be made on the basis of experience and practice codes without the computer aids. Also, the product designer, process planner and die designer may have to spend many hours consulting handbooks, going through empirical formulae, perusing tabulated and graphical information, and making ∗ Corresponding author at: Department of Mechanical Engineering, Hindu College of Engineering, Industrial Area, Sonepat, 131001 Haryana, India. Tel.: +91 130 2210756; fax: +91 130 2210755. E-mail address: [email protected] (S. Kumar).
0924-0136/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jmatprotec.2005.09.001
calculations before arriving at workable designs. Beside this, the manual method of testing manufacturability of the part is tedious and time consuming, and often does not yield optimum results. There exists therefore, the need of developing low-cost knowledge-based systems [3] that are capable of providing intelligent advice to the planners of sheet metal operations especially one employed in the small-scale industry. In recent years the computer-aided procedures [4–8] are being increasingly utilised to ameliorate the above difficulties. The specific objectives of the present work is the development of a knowledge-based system for assisting the product designers, process planners and die designers to check the correctness of the geometrical features of the part on manufacturability basis. The AutoLISP language has been utilised in the proposed knowledge-based system, since it can be interfaced with AutoCAD for computer-assisted drafting, designing and manufacturing of die components for sheet metal operations. For consultation, the user loads the knowledgebased system into the prompt area of AutoCAD. The proposed system generates friendly prompt eliciting from the user for data pertaining to the job at hand. The system output includes recommendations on suitability of geometrical features of the part for
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
required manufacturing operations. The system is flexible and its knowledge base can be extended and modified as old manufacturing facilities are discarded or newer ones are acquired in a particular enterprise. 2. Considerations for checking manufacturability of the part As a first step in the planning of manufacture of a sheet metal component, it is useful to check whether certain of its design features are conducive to ease of manufacture. Such checks are useful to avoid manufacturing defects, section weakness, and need of new dies, tools or machines. Dimensions and location of internal and external features such as holes, extended holes, internal contours, external contours, cuts, notches, bosses, cups, slots and bends should be tested against rules of good practice. One should consider the following information while checking manufacturability of the part: (a) The corner radius on sheet metal parts should be at least 0.7 times of sheet thickness. (b) The width of recesses or slots or projections along blank profile should be minimum 1.2 mm. (c) The permissible minimum diameter of piercing depends on the type of sheet material, shape of holes and sheet thickness. For piercing round holes, the diameter should not be less than 0.5 mm for hard steel sheet material and 0.4 mm for soft steel, brass or aluminium sheet material. The size of a square or rectangular hole should not be less than 0.35 mm for soft steel, brass or aluminium sheet material. (d) The spacing between holes on sheet metal parts should be at least 2.0 times of sheet thickness. 3. Development of the knowledge-based system The procedural steps [9] in the development of the proposed knowledge-based system (KBS) involve selection of knowledge representing language, Collection of information on manufacturability, preparation of knowledge base and development of user friendliness. A brief description of each step is given below. 3.1. Selection of knowledge representing language Early expert systems were written in language interfaces derived from FORTRAN. Later on, object-oriented languages such as KEE, OPS, PROLOG, TURBO, PROLOG and LISP were developed specifically for the knowledge-based systems [10]. LISP and PROLOG have won wide acceptance for building such intelligent systems [11]. But the user of these languages encounters difficulties when handling design problems involving graphical information. For this reason, AutoCAD [12,13] and AutoLISP [14,15] have found greater acceptance in design and manufacturing, evaluation of design alternatives, and creation of drawings. Expert system applications involving graphical data can be built by combining AutoLISP and AutoCAD [16]. For this reason, the present system makes use of AutoLISP and AutoCAD facilities.
65
3.2. Collection of information to check manufacturability Information to check manufacturability are essentially collection of bits and pieces of published, or unpublished, analytical or empirical knowledge from a variety of sources including experienced product designers, process planners and die designers, shop floor engineers, and handbooks, monographs, research journals and industrial brochures. The chief data sources utilised during the present investigation are listed in References [17–25]. Information on manufacturability checks was culled from industrial experts by holding discussions on typical problems and letting the experts talk about the approach, formulae and thumbrule relied upon by them. They were asked as to how and why a particular decision was reached. This was done to identify the parameters influencing the manufacturability of the part for a particular decision. The data, facts and judgment obtained from each expert were recorded, transcribed and then checked with other experts before formalising into production rules. The experts were also observed while working. Design recommendations contained in the “manufacturability manual” of the company can also be incorporated in the form of production rules. 3.3. Preparation of knowledge base The common systems of creating a knowledge base are through either production rules or frames [26]. The production rule-based system is the earlier and more popular approach to represent analytical, heuristic or experience based knowledge. The production rules are usually of the IF (action)–THEN (conclusion) kind. The frame based knowledge representation scheme uses a hierarchy of frames where each single frame is a template that holds a unit of data, fact, rule or hypothesis. The knowledge base of the proposed system is based on production rules. The production rules are carefully structured by considering both the domain knowledge as well as shop specific information. These rules may be arranged either in an unstructured (arbitrary) or a structured manner. In the latter case, the rules tend to be simpler and briefer because they are designed to “fire” in some hierarchical manner. The sequencing of rules of the proposed KBS is unstructured. The production rules have been encoded with the help of AutoLISP language. This arrangement allows insertion of new production rules even by relatively less trained knowledge engineers. For searching a solution to a particular problem, two strategies called as the forward chaining and backward chaining are generally used [27]. In forward chaining, the user interactively supplies system data or facts about the problem to be solved. The system searches the IF conditional data to determine which rules are satisfied by the given facts. Whenever a particular IF condition is found to have been satisfied, the THEN portion of the rule is gets activated leading to a conclusion or an advice. The search is continued till the complete solution is found. On the other hand, in backward chaining, the search proceeds ahead or moves backward to support a hypothesis or a goal. The proposed production rule-based KBS makes use of forward chaining. A sample of the production rules incorporated in the present KBS is given in Table 1.
66
Table 1 A sample of production rules included in the proposed knowledge base system IF
THEN
1 2 3 4 5
Minimum corner radius in mm ≥0.7 times sheet thickness Minimum corner radius in mm <0.7 times sheet thickness Width of recesses or slots or projections along blank profile ≥1.2 mm Width of recesses or slots or projections along blank profile <1.2 mm Sheet material = ‘Hard Steel’ and shape of hole = round and 0.5 mm ≤minimum hole diameter ≥1.3 times of sheet thickness Sheet material = ‘Hard Steel’ and shape of hole = round and minimum round hole diameter <0.5 mm Sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ shape of hole = round and 0.4 mm ≤minimum round hole diameter ≥sheet thickness sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ and shape of hole = round and minimum round hole diameter <0.4 mm Sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ and shape of hole = square or rectangular and 0.35 ≤minimum dimension of hole ≥0.7 times of sheet thickness Sheet material = ‘Soft Steel’ or ‘Brass’ or ‘Aluminium’ and shape of hole = square or rectangular and minimum dimension of hole <0.35 mm Minimum hole pitch ≥2.0 times sheet thickness Minimum hole pitch <2.0 times sheet thickness Minimum bend corner radius in mm ≥3.0 times sheet thickness and 2
“Accept the corner radius” “Set minimum corner radius = 0.7 times sheet thickness” “Accept width of recesses or slots or projections” “Set width of recesses or slots or projections = 1.2 mm” “Accept the diameter of hole”
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
“Set minimum diameter of hole = 0.5 mm” “Accept the diameter of hole” “Set minimum diameter of hole = 0.4 mm” “Accept the dimension of hole” “Set the minimum dimension of hole = 0.35 mm” “Accept hole pitch” “Set minimum hole pitch = 2.0 times sheet thickness” “Accept the bend corner radius” “Set minimum bend corner radius on part = 3.0 times sheet thickness” “Set minimum bend corner radius on part = 2.5 times sheet thickness” “Set minimum bend corner radius on part = 1.5 times sheet thickness” “Set lead end scrap web allowance in mm = 1.25 times sheet thickness” “Set minimum lead end scrap web allowance = 1.5 mm” “Set minimum front/back scrap web allowance = 1.5 mm” “Set lead end scrap web allowance in mm = 1.75 times sheet thickness” “Set front/back scrap web allowance in mm = 1.75 times sheet thickness”
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
S. No.
S. Kumar et al. / Journal of Materials Processing Technology 172 (2006) 64–69
3.4. Development of user friendliness The purpose of development of user friendliness is two-fold. It enables the user input the essential the job related data to the system and it displays the intelligent advice for the user’s benefit. This is achieved by making the interface flash prompts at appropriate stages during a consultation inviting the user input data items. It also displays messages or items or advice on the computer screen at appropriate times. The user is guided in a friendly manner throughout the consultation on how to proceed further at each different stage. 4. Description of the proposed knowledge-based system Heuristic knowledge for the construction of the proposed KBS was obtained from various sources as discussed earlier. Examples of the production rules based on the knowledge so
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acquired are given in Table 1. These rules were encoded in AutoLISP. The system incorporates an interface for displaying friendly prompts to guide the user during a consultation session. The chief purpose of the prompts is to ask the user to input the needed data. The user initially loads the program by using the command (LOAD “A: PARTDGN.LSP”) in prompt area of AutoCAD. The program, after compilation, is ready for serving the user. As soon as the user has supplied sufficient data during a consultation, the program scans through the production rules one after the other. Whenever the IF condition in a production rule gets satisfied, the module displays the THEN advice for benefit of the user. The proposed KBS described above was tested by considering the problem of checking manufacturability of the part for the two real industrial components shown in Figs. 1 and 2. Typical prompts, user responses and the recommendations obtained by the user during the execution of the program for the example problems are given through
Fig. 1. Example component 1 (dimension: mm, sheet material: brass, sheet thickness: 0.6 mm).
Fig. 2. Example component 2 (dimensions: mm, sheet material: brass, sheet thickness: 3.0 mm).
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Table 2 Typical prompts, user responses and expert advice during execution of the proposed knowledge base system for example component 1 S. No. 1 2 3 4 5 6 7 8 9 10
Prompt
Example data entry
Advice to the user
Please enter sheet material Please enter sheet thickness in mm Please enter the minimum corner radius sheet metal part in mm Please enter minimum width of recesses or slots or projections along blank profile in mm Please enter shape of holes on the part Please enter minimum dimension of round hole on part in mm. Please enter minimum dimension of rectangular hole on part in mm Please enter minimum hole pitch in mm. Please enter the shape of component edge Please enter the maximum dimension of the component in mm (length/width)
Brass 0.6 0.001 1.6
“Set minimum corner radius on part in mm = 0.42” “Accept width of recesses or slots or projections”
Round and rectangular 2.5 5.2 6.1 Straight 62.0
“Accept the dimension of hole” “Accept the dimension of hole” “Accept hole pitch” “Set lead end scrap web allowance in mm = 1.5” “Set front/back scrap web allowance in mm = 1.5”
Table 3 Typical prompts, user responses and expert advice during execution of the proposed knowledge base system for example component 2 S. No.
Prompt
Example data entry
1 2 3 4
Please enter sheet material Please enter sheet thickness in mm Please enter the minimum corner radius on sheet metal part in mm Please enter minimum width of recesses or slots or projections along blank profile in mm Please enter shape of holes on the part Please enter the minimum diameter of round hole on part in mm. Please enter minimum hole pitch in mm. Please enter the shape of component edge Please enter the maximum dimension of the component in mm (length/width)
Brass 3.0 1.75
5 6 7 8 9
Tables 2 and 3. The recommendations obtained were found to be reasonable and very similar to those actually used in industry (Indo-Asian Fuse Gear Ltd., Murthal, Haryana, India for the component shown in Fig. 1 and Anurena Tristar Ltd., Delhi, India for the component shown in Fig. 2). Notable features of the proposed system are its lowest cost and the linking of the die design process with quick drafting of die assembly and die components. The knowledge base of the system can be easily modified or expanded by changing in the existing production rules or adding new rules. Additional modules can also be added to meet the changing requirements of the production unit.
Round 5.0 14.20 Straight 245.27
Advice to the user
“Set minimum corner radius on part in mm = 2.1” Not applicable
“Accept the diameter of holes” “Accept hole pitch” “Set lead end scrap web allowance in mm = 5.25” “Set front/back scrap web allowance in mm = 5.25”
ple dies, compound dies, progressive dies and combination dies for carrying out operations such as piercing, blanking, notching, forming, cropping, shearing, trimming, clipping, parting, slitting, perforating, bending and drawing. Illustrative examples have been included for demonstrating the usefulness of the proposed system. The knowledge base of the proposed system can be modified depending upon the capabilities of a specific shop floor. The low-cost of the system makes it affordable for planners working in small and medium-sized enterprises.
References 5. Conclusion Knowledge for checking manufacturability of sheet metal part, obtained from product designers, process planners, die designers, handbooks, catalogues, and brochures has been analyzed, tabulated and incorporated into a set of production rules. The procedure used for constructing the knowledge base system is explained at some length. The proposed knowledge base system has been designed as a low-cost alternative for use in by sheet metal planners and is capable of checking manufacturability of the part for sheet metal operations. Application of the proposed system is illustrated through examples. The system imparts intelligent advice to the user on product manufacturability point of view at the initial stages of die design. The proposed system applies to situations involving the use of sim-
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