Development of Optimal Cutting Plan using Linear ... - ijimt

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International Journal of Innovation, Management and Technology, Vol. 1, No. 5, December 2010ISSN: 2010-0248Figure 13: ArcherTool LP Model Solution Screen Shots - No Direction Constraint490
International Journal of Innovation, Management and Technology, Vol. 1, No. 5, December 2010ISSN: 2010-0248Figure 14: LINGO8.0 LP Model Solution Screen Shots - No Direction ConstraintFigure 15: ITEMIZER9 Graphic Solution Screen for Cutting Stock OptimizationVI. CONCLUSIONSFrom the tables & graphs compiled in earlier sections, it isevident that larger sizes of stock sheet can yield into higherutilization with lesser wastage as obvious. The percentageyield is at maximum when stock sheet size is integral multipleof the Least Common Multiple (L.C.M.) of lengths & widthsof items being cut. Moreover, it is revealed that total yieldand, hence, wastage fraction depends upon the cuttingdirection, orientation and divisibility of respective stock anditem length and width.LINGO8.0 has an advantage of integer constraint optionon the decision variable, which is not available from ArcherTool (LP Package). On the other hand, the latter isuser-friendly and easy-to-use as no specific programmingsyntax is required and the only input required is of the valueof coefficients of decision variables. The MATLABalgorithm provides the optimal value of the decisionvariables with the layout display for enhanced visualizationof the cutting plan whilst the ITEMIZER9 requires thequantity input of the decision variables and then displays thecorresponding layout of the cutting plan. In addition toconformity of the results from MATLAB Algorithm withother approaches, further verification/validation of allapproaches has been achieved through comparison with aknown case in reference [15].Blanking outline size from large stock size for specificcomponent is very common in almost all types ofmanufacturing set-ups from woodworking, steel fabricationto aerospace industry. So, this work will help enhanceproductivity and profitability of a manufacturing industrythrough optimum utilization of available material,minimizing scrap/trim losses and inventory storage costs bymeeting applicable constraints and customer’s needs.This work may also be utilized for assessing differentstock sizes or to order specific stock sheet size yieldingmaximum utilization and minimum waste while meetingcustomer’s demand. As the MATLAB code/LP model can beapplied prior to actual cutting/placing of procurement orderfor appropriate stock sheet, one can save precious materialand curtail its budget keeping in view the worldwideeconomic crisis.491
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Development of Optimal Cutting Plan using Linear ... - ijimt

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