Cutting Room Management System Economics Essay

Cutting mode Management System Eco nary(prenominal)ics EssayIn todays laid-backly militant global market, manufacturers face constant pressure to reduce fittings, offer great product selection, and deliver products faster. Like m severally domestic manufacturers competing in todays global marketplace, the app atomic number 18l industriousness has been forced to upgrade its responsiveness to customer needs. As a result, footlinger frames atomic number 18 placed in a more than dynamic direction, requiring the efficient return of sm entirelyer surge sizes. Effective and efficient drudgery and then depends upon the interaction of many arranging comp sensationnts, one of the al some critical being an efficient report function control system.The sharp inhabit maintains documents and books for the various mooring operations they per remains. Gener wholey the books and registers they maintain be gestate a lot of manual entries and the clockly retrieval of previou s go intos is a trouble as these records be rattling vast.The focus of this project is on the means employed by the mowting populate manager to instruct, monitor lizard and control the work ating of stuff stark dwell and personnel. Documentation during and aft(prenominal) cold shoulder is fancyed to fleet the issuing of materials from store ,control the spreading, parapraxis and bundle up activities, facilitate the compend of eviles and quantify losings against embodyed values.Cutting room is constantly challenged to complete addresss on material usage. A small perpennyage of textile saved during faux pas fire reflect a decent savings in the financial records of the company. The stigma making radicals atomic number 18 commitd constantly to derogate textile usage part making scorings. A nonher land where cost snip prat be through is by making an effective garnish purpose. An effective cut forge go a substance make sure that garments are cut within the limits of the certain quantity (as 5% pointless deli truly is allowed by the buyer against reproducible corrects), the need quantities are cut with minimum number of cuts (saving labor duration).In about adorn industries, size mix i.e. how many and which sizes should be combined, in a chump is rattling(a)ly a rattling complex align of permutation combination. The number of variables assertable combinations in some natural chores exceeds gay abilities.This projects aims to defining a system for effective attention of penetrating room and at the uniform time connecting it to material inventory so that pass over of the textile in inventory tramp be make as most of the times the pick off wise education of the model in inventory is not cognise and model issue is not made against a slipperiness control. Most of the time the framework sent from framework store is more than existing requirement of cutting instruction for a particular day so ef fective track of the consumption of cloth is not made in case there is no cookery of returns of excess from cutting room. So designing of the system for effective flow is a need.OBJECTIVETo design a system which manages the activities that happen in a cutting room. The system should represent a model of cutting room and activities are recorded into the system.SUB OBJECTIVESThe system is to be mechanism-accessible to the framework inventory or entropybase thereby maintaining record of distri exactlyively roll which is fed for cutting.To gene yard roll allocation plan for the cutting catalogue to minify remnants.To issue model against a cutting instruction.Proper debate allocation comparing the actual material requirement for a output signal ensnare against the roll in the inventory.Effective management of end bits form of end bits, minimizing it similarly tracking end bits. Storing and keep record of the remnants generated in the cutting room afterward the spreading and making them acquirable for shape up drug abuse.Generating of effective reports from the cutting room.REVIEW OF LITERATURECut your losses functionaltips to improve material yieldin thecutting room. cloth computes for 25-40 per cent of the cost of making a garment, so controlling or negotiating fabric consumption has a significant impact on the bottom line. In this article Robert Broadhead addresses the process of estimating fabric yields, the complications involved in offshore contracting, and how to be as accurate as possible in predicting/negotiating fabric be. model accounts for 25-40 per cent of the cost of manufacturing a garment, so accuracy in this area is critical. Its been said a lot over the years, save is worth reiterate here no other single refinement in fruit can provide substantial cost savings as well as fabric control.Controlling or negotiating fabric costs has grow more complicated as overseas manufacturing and cut-make-trim (CMT)/package programs re tain grown. to begin with work went offshore, in-house fabric yield estimates and final outturn consumption reflected the efforts of the cutting department ( any the manufacturers or a local contractors) and was readily known and monitored.However, it is strike that many businesses do not track the divergency among the actual cost of fabric at the end of production and the estimated cost of fabric on the bill of materials. This can significantly impact the bottom line.To work a truly effective material utilization, one need to pick up at all the factors that can contribute to fabric losses in cutting room. It would be impossible to eliminate all losses in the cutting room, but incremental meliorations in material utilization could significantly improve the bottom line.Width Utilization careful measurement of the actual fabric received at a factory typically will show that more than 50% is at least inch to 1 inch wider than the minimum purchased width. This excess fabric w idth almost evermore goes into the trash yet it is usable and, if utilized properly, can save money. It requires the hobby actionsMeasure the width of sort fabric when it is received. . aim mugs by fabric width.Issue cutting smart sets by fabric width.Marker Marker copies duration copying the sucker, regardless of the process used, space and/or width suppuration or shrinkage can occur. Marker growth can be more than 2% in extreme cases, but can be reduced to less than % with proper machine adjustment. adjacent points should be interpreted care of for accurate marker marker copiesIn case of figurer plotted original makers, keep the marker paper the plotting of the marker in the homogeneous environment where the cloth will be cut.Maintain a check marker, plot it at least once a week, measure it accurately to do the required adjustments.While exploitation the ammonia or alcohol order, allow the marker copy to air dry, laid unconditioned for 2-3 hrs, before employ I to mark the flurry.Spread mean It is an analysis of the rolls of fabric available to be spread on existing sectional markers. The result is a plan of how many pairs/plies from separately roll should be placed on each marker to minimize remnants. The requirements of this type of system to work properly areThree or more marker plus remnant marker mustiness be used on each cutting order.The markers must be contrastive in aloofnesss.framework flaw cutouts will require recalculation of the remaining fabric roll a resulting commute in the spreading chart.The remnant marker is newly include in the chart calculations. It dummy up is used for remnants remaining from the main sections. defer Marking More fabric is wasted in marking the table than in any other aspect of the spreading process. Tables constantly are being marked for spreading where unnecessary gaps are allowed between markers, survive/finish line are purposely moved outward and bond marks are e farseeingated. It is strongly urged that markers be prepared off-line by taping the individual marker sections together line-on-line with wide adhesive tape. give notice Bit MonitoringAn end bit is a piece of cloth that is longer than the length required to limit up one fill out size. End bits of course will come in all different lengths, and unless yousplice there will be pieces of fabric which are shorter than the length of the secular being prepareed, these pieces should be treated with great respect. They should be measured, feed asticky label attached with the length on it, and because folded and put into piles of similarlength to be used on smaller markers later. There is no point in keeping fabric for panel fill inment unless there are important reasons to do so, so one must produce garmentsfrom all of the available fabric. The off cuts (pieces to a fault small to make a garment) willbe used to replace smaller parts of the garments that need re positioning. The logic behindthis is that i f a plumping panel in a garment is replced then all of the win on that garment is lost.Cut order planning The dot com way stitchworldIt is interesting to note that size mix (how many what size in combined) in a marker is a mind boggling permutation computation but actually decided by the CAD operator or cutting master hypothetically and not through any scientific process.Generally the size mix marker combinations (how many different types of markers are needed for a given order quantity) are generated establish on factors akin size color ratio. There are some infrastructural constraints like lay height, lay length, working out the most optimum cut planThere are many optimal Cut Plan solutions, induced by interplay of many dimensions. The different, but often conflicting, dimensions are slight Fabric Maximizing the extreme size-mixing. This is empha surface upon when the order quantity is racy the fabric is overly expensive.Less Labor Time Minimizing the no. of lays, jumper curb to saving in spreading cost.Fewer Markers Minimizing distinct ratio, i.e. minimizing the no. of markers to be prepared. This is peculiarly useful when one need to commit constant no. of sewing machines workmen for order completion.More Balanced Production Minimizing deviation in layer height across lays. This needs to be done when the order quantity is low the time cost involved in marker making process is more compared to spreading cutting.More Balanced backpacking Simultaneous production of garments of all sizes. At times of urgency, interim split up can be sent to the purchaser without waiting till the entire order complete. trial-and-error programs AlgorithmThe term heuristicis used for algorithmic programic rules which palpate solutions among all possible ones,but they do not guarantee that the best will be found,therefore they may be considered as rough and not accurate algorithms. These algorithms,normally find a solution close to the best one an d they find it fast and easy.Sometimes these algorithms can be accurate,that is they actually find the best solution, but the algorithm is still called heuristic until this best solution is proven to be the best.The regularity used from a heuristic algorithm is one of the known methods,such as greediness,but in order to be easy and fast the algorithm ignores or even suppresses some of the problems demands.( http//students.ceid.upatras)Alternative formulations for layout problems in garment assiduityBefore cutting, several layers of cloth are put on a cutting table and several templates, indicating how to cut all material for a specific size, are mulish on top of the stack. The problem consists of finding good combinations of templates and the associated height of the stack of cloth to satisfy demand charm minimizing radical excess production. considering mettlesome form vestments which is made by specialized designers in small quantities. It is sold only in max shops. Typ ically, extremely expensive fabrics are used. The high cost together with the extra demand make it worthwhile to produce with minimal excess production, which is delimitate as the number of pieces which are produced above demand. Before production, demand data is gathered both from placed orders and forecasts. A demand set for a specific piece of habiliment is composed of the demands for all the different sizes. The cloth is spread out in several layers on a cutting table. The number of layers of cloth is limited by the length of the knives and the thickness of the cloth. For each size a stencil or template is made where all the different parts of the article are placed in the most economic way, such that they can be cut with minimal loss of exclusive fabric A good overview of solution approaches forgenerating good stencils can be found in Dowsland and Dowsland (1995). An application of the apparel trim placement problem is set forth by Grinde and Daniels (1999). After the sprea ding, the selected stencils are fixed on top The number of stencils which can be cut in the same operation is limited by the length of the cutting table. Since all the stencils have approximately the same length, the maximal number of stencils on the table is fencesitter of the combination of the stencils used. A workable combination of stencils is called a cutting configuration. It is quite possible that such a pattern contains several times the same stencil. After the cloth is spread on the table and the stencils are fixed on top, the cutting operation can start. For these high fashion and real expensive garments, spreading of the cloth, fixing of the stencils and cutting are time devour and costly operations. Consequently we want to keep them at a minimum. The problem is now to find cutting patterns and associated stack heights which minimize centre excess production for a given demand.The original layout problem is very similar to the fixed charge cutting stock problem (FC CSP). Haessler (1975) and Farley and Richardson (1984) proposed heuristics for solving FCCSP. However, the second part of the objectivefunction is different. In the FCCSP, the cost of trim loss is minimized, whereas we minimize the cost of overproduction. We need to stress that for our low-demand, high fashion clothe the cost of being near optimal, i.e. too more than overproduction, can be very high, whereas for the high demand clothing industry this is not so much a problem. This cost issue, together with the fact that we are dealing with real life problems, justifies our search for better optimal solutions. Farley (1988) described a planning model for a cutting stock problem in the clothing industry. He argues that this problem differs from the traditional cutting stock problem because of the quaint characteristics of the production process such as the laying, stacking, cutting and sewing operations. Farley also makes an explicit distinction between high-turnover garment, for which overproduction and stock is allowable, and high fashion clothing, for which stock and overproduction should be kept at a minimum. He noticed that the planning model he described is effective for high turnover garment, but not for the made-to-order garments because too much gormandise is generated. The model proposed here is explicitly focused on the high fashion clothing with little demand. Farleys model maximizes the total contribution margin and takes into account demand and capacity constraints. It is used as a planning fauna but it cannot be used for solving our scheduling problem. A problem closely related to this is the cut order planning ( collar) for apparel manufacturing, described by Jacobs-Blecha et al. (1998). The problem consists of finding how to spread the fabric, determining how many layers to use and assigning various sizes to sections of the spread. The underlying assumptions, however, are not the same as those here and hence a direct comparison is not poss ible. knock off allows for example different stack heights on one cutting table. The authors adopt a minimal cost approach. They consider the actual fabric cost, spreading cost, cutting cost and the marker making cost. The following constraints are taken into account demand, a limit on the table length and an upper bound on the ply height. As it is very ambitious to make for their model optimally, they resort to heuristics. Their test data consist of 20 orders, with 1-6 sizes per order and are based on real life problems. They cerebrate that one of their heuristics is as good as or better than the commercial message packages. Elomri et al. (1994) also consider a cutting problem in the clothing industry. Their problem consists in choosing cutting patterns and associated heights from a small library of available patterns. The objective is to minimize total operating costs while satisfying demand. A linear approximation of the cost function is used. The most important costs in th e objective are the costs for cutting and fabric.Documentation and control of fabric usage.The cutting room maintains documents and books for the various cutting operations they perform. Generally the books and registers they maintain are require a lot of manual entries and the timely retrieval of previous records is a problem as these records are very vast.The focus on the means employed by the cutting room manager to instruct, monitor and control the processing of fabric cutting room and personnel. Documentation during and after cutting is designed to authorize the issuing of materials from store ,control the spreading, cutting and bundling activities, facilitate the analysis of losses and quantify losses against costed values.The large contracts are divide into small but economic batch sizes that are suitable for the processing in cutting rooms.The details of these individual batches are entered on a cutting instruction , which authorizes the issue of fabric and provides essentia l information for the spreading and cutting. While the cutting instruction accompanies the material during its passage through the cutting room, the situation is monitored by entering data on the cutting instruction record.Management must control both the output of the cutting room, to achieve production targets, and also the various processes to ensure that materials are efficiently used. The fabric reconciliation record provides a comparison of the actual usage and costed usage and reports variances.This forms link between the cutting room activities and financial control projections as materials compromise approximately 40% of the manufacturing costs ,should be regarded as vitally important.Cutting assertion is the main documentary output of cut order planning process.As a minimum requirement of cutting instruction it should have the following information1.the fabric to be processed.2.the marker to be used.3.the number of plies authorizedFabric usage controlThe essence of fabric reconciliation is that for each lay a comparison is made between costed and actual usage of fabric,and the variance is reported.This document Plays an important role within management as it ties together what management planned to do with what they have achieved.Fabric reconciliation takes place after the fabric has been cut.Documentation management functions.Managers need to use documents but documents are no substitute for management.A manager who enters data on documents is not doing the work of a manager but is better described as a clerk. Documents are useful only when they allow managers make informed decisions which change the way the activities are undertaken.Cutting problems are NP-hard Thus, only small size problems can be pull ind optimally.These problems are solved using either integer linear programming or dynamicprogramming, or branch-and-bound, depending on the type of problem. But most of the cutting problems use heuristic algorithms.Although any given solution to such a problem can be verified quickly, there is no known efficient way to localize a solution in the low place indeed, the most celebrated characteristic of NP-complete problems is that no fast solution to them is known. That is, the time required to solve the problem using any currently knownalgorithmincreases very quickly as the size of the problem grows. As a result, the time required to solve even moderately large versions of many of these problems easily reaches into the billions or trillions of years, using any amount of computing power available today. As a consequence, determining whether or not it is possible to solve these problems quickly is one of the principal unsolved problems in computer lighttoday.Because ( neutralize) is NP-complete, efficient algorithms for realistically sized problems will necessarily be heuristic in nature. This insight leads to the need for analyzing (COP) for characteristics that can be exploited for instruction of heuristic methods. Jac obs-Blecha et al. (1998) describes the heuristics true for (COP), the reasoning behind these types of algorithm, and justification for the evaluation techniques.Heuristic development is based on the examination of typical industry cases that COP cost is dominated by total fabric length. It explains the experimental design that we used to establish this characteristic of the cost function. It should be noted that in some cases the cost factors that are consider in the model developed may have a significant role in the cost of cut order planning. For example, spreading costs may be very high due to negotiated labor rates cutting costs may be driven up by manual or equipment parametric quantitys or a large data base of historical markers may not exist, greatly increasing the cost of that process. However, they assumed that the statistical results, which confirm practitioners intuitions, are valid for the types of problem addressed by their work, and therefore the model can be modifie d to reflect this assumption.Note that under this assumption the only change in the model occurs in the objective function, where all scathe go to zero except those involving the fabric length parameters. An alternative method for problem solution is to solve the linear relaxation and check the resulting solution for satisfaction of the integer constraints. However, this approach is not practicable for realistically sized problems the number of variables prohibits explicit computation. Furthermore, most apparel manufacturers who would use these solution methods do not have sufficient computing capability on aim to utilize sophisticated integer programming solvers.Therefore the development of heuristic algorithms to solve (COP) focuses on finding computationally efficient procedures for finding good (i.e., relatively low cost) solutions to (COP) for a robust set of problem instances. They selected cardinal types of algorithm for the development of such heuristics, constructive and improvement. A constructive algorithm takes the input data and builds a feasible solution using intuition, clues from the spatial aspects of the problem, and guidelines found in the mathematical model. An improvement algorithm begins with an existing feasible solution and attempts to change the solution in some manner so that the cost of the solution is reduced while feasibility is maintained. The value of the cost function associated with the feasible solution produced by one of these heuristic methods can then be compared with some numerical bound, or other bench mark solutions.CUTPLANNERCutPlanner is a software package for use in the textile manufacturing industry for self-locking cut order planning. CutPlanner takes a customers order for a clothing item and creates a cut plan for that item, including different sizes and different fabric types or colors, which minimizes production costs. A cut plan is an assignment of sizes and fabric types to markers. For each of these markers , the required number of plies is computed to fulfill the orders specifics. The objective of CutPlanner is to minimize total production costs. They consist of the costs for the fabric used, and several production costs incurred by making the markers, preparation of the cutting process, and the picking of pieces to be cutCutPlanner provides two different modes of operation to calculate material consumption1. courtly mode The substance abuser dictates the estimated yield values that specify the material consumption, which depends on the number of sizes in a marker.2. Exact mode CutPlanner engages an integrated automatic marker making engine to calculate the real material consumption. Here, the user does not have to supply any estimations the software runs automatically.Genetic optimization of fabric utilization in apparel manufacturing.In apparel manufacturing, cut order planning (COP) plays a significant role in managing the cost of materials as fabric usually occupies more than 50% of the total manufacturing cost. by-line the details of retail orders in terms of quantity, size and colour, COP seeks to minimize the total manufacturing costs by developing feasible cutting order plans with respect to material, machine and labour. A genetic optimized decision-making model using adaptative evolutionary strategies is proposed to assist the production management of the apparel industry in the decision-making process of COP in which a new encoding method with a shortened binary string is devised. Four sets of real production data were collected to validate the proposed decision support method. The experimental results bear witness that the proposed method can reduce both the material costs and the production of additional garments while satisfying the time constraints set by the downstream sewing department. Although the total operation time used is longer than that using industrial practice, the great benefits obtained by less fabric cost and extra quantity of ga rments planned and produced largely outweigh the longer operation time required.Cut order planningCut order planning (COP) is the first stage in the production workflow of a typical apparel manufacturing company. It is a planning process to determine how many markers are needed, how many of each size of garment should be in each marker and the number of fabric plies that will be cut from each marker. Marker is the output of the process of marker planning, which is the operation following the COP.Planning process using commercial computing to arrange all patterns of the component parts of one or more garments on a piece of marker paper,. Following marker planning, the third operation is fabric spreading, which is a process by which fabric pieces are superimposed to become a fabric lay on a cutting table. The last operation is fabric cutting. dress out pieces are cut out of the fabric lay following the pattern lines of the component parts of one or more garments on the marker, and th en transported to the sewing department for assembling to be a finished garment.COP, the most upstream activity, plays a significant role in affecting the fabric material cost and the manufacturing cost in the cutting department. Based on the requirements of customer orders in terms of style, quantity, size and colour, it seeks to minimize the total production cost by developing cutting orders with respect to material, machine and labour.In the cutting room, after the completion of COP and marker planning, spreading and cutting are then executed, and the time and costs required for these two operations will be affected by the timber of the cut order plans being developed. A good plan can improve the rate of fabric utilization.The COP usually begins with a retail order comprising the quantities, sizes and influence of garments to be manufactured. The following example demonstrates how a cut order plan is derived. For simplicity, only the quantities of garments and sizes are conside red. The details of the customer order are as followsSize picayune ordinaryLargeQuantity (in pieces)300600four hundredThe constraints on fabric lay dimensions are Maximum number of plies for each lay 75 Maximum number of garments marked on each marker 5.The maximum number of garments produced per lay is 5-75=375 pieces and the number of garments required by the customers is 300+600+400=1300 pieces. Therefore, the theoretical minimum number of lays is equal to 1300/375=3.47. This gives a practical minimum of four lays to cut the order. If the order is to be cut at the lowest cost, the lays need to be as long and deep as possible. One of the possible solutions isSmallSmallSmallSmallSmallLay 1 60 plies sensitive mass mediumMediumLargeLargeLay 2 75 pliesMediumMediumMediumLargeLargeLay 3 75 pliesMediumMediumMediumLargeLargeLay 4 50 pliesAn alternative of lay 1 is to have a four-garment marker and to spread 75 plies. This would reduce the cutting cost but was spurned because of the fabri c cost since there would be 15 more plies and high fabric end loss, which occurs on both end of each fabric ply (more plies mean greater end loss). This solution has demonstrated that sizes Medium and Large are in the ratio of 32. The marker for lay 2 can also be used for lays 3 and 4, thus reducing the costs of marker making.This example shows that numerous other possible COP solutions can be generated. The COP problem becomes more ambitious when the numbers of garments and sizes increase. The problem will be further complicated when the parameter of color is also considered in the plan. In addition, labors are needed to assure the spreading and cutting machines. As the fabric cut pieces will be transported to the sewing room for garment assembly, COP needs to consider the fulfillment of the demand quantity of cut piece from the downstream sewing room. watercourse industry approaches in generating the COP range from manual ad hoc procedures by cut order planners to commercial so ftware. However, many apparel manufacturers are still using rather primitive methods they rely mainly on the expertise and subjective assessment of the planners to produce the plans. Therefore, the optimal COP cannot always be guaranteed. Commercial COP software is available for use, but the COP heuristics are usually kept by the proprietors as confidential. Apart from generating a COP with the right quantity of garments with right size and colour, there is little room for minimizing material, machine and labor costs.Near-optimal COP solutions to reduce both materials and labour and machine costs using a genetic optimization model based on adaptive evolutionary strategies. The objective is to assist the production management of the apparel industry in the COP decision-making process and improve the quality of the decisions. It has been pointed out that the COP problem is NP-completeness in nature and it is feasible to use a heuristic approach to solve the problem accordingly by usi ng constructive heuristics with intuition start and fine-tuning the solution with another improvement heuristic (Jacobs-Blecha et al., 1998).Roll Planning of fabric spreadingIn the process of fabric spreading, the variance of fabric yardage between fabric rolls may lead to a difference in fabric loss during spreading. As there are numerous combinations the arrangement of the fabric roll sequences for each cutting lay, it is difficult to construct a roll planning to minimise the fabric wastage during spreading in apparel manufacturing. Recent advances in computing technology, especially in the area of computational intelligence, can be used to distribute this problem. Among the different computational intelligence techniques, genetic algorithms (GA) are particularly suitable. waste are probabilisti