DETC A SYSTEMATIC METHODOLOGY FOR ACCURATE DESIGN-STAGE ESTIMATION OF ENERGY CONSUMPTION FOR INJECTION MOLDED PARTS

Transcription

1 Proceedings of he ASME 2010 Inernaional Design Engineering Technical Conferences & Compuers and Informaion in Engineering Conference IDETC/CIE 2010 Augus 15-18, 2010, Monreal, Quebec, Canada DETC A SYSTEMATIC METHODOLOGY FOR ACCURATE DESIGN-STAGE ESTIMATION OF ENERGY CONSUMPTION FOR INJECTION MOLDED PARTS Alexander Weissman Deparmen of Mechanical Engineering Universiy of Maryland College Park, Maryland Sayandra K. Gupa Deparmen of Mechanical Engineering and Insiue for Sysems Research Universiy of Maryland College Park, Maryland ABSTRACT Today's ubiquious use of plasics in produc design and manufacuring presens significan environmenal and human healh challenges. Injecion molding, one of he mos commonly used processes for making plasic producs, consumes a significan amoun of energy. A mehodology for accuraely esimaing he energy consumed o injecion-mold a par would enable environmenally conscious decision making during he produc design. Unforunaely, only limied informaion is available a he design sage. Therefore, accuraely esimaing energy consumpion before he par has gone ino producion can be challenging. In his paper, we describe a mehodology for energy esimaion ha works wih he limied amoun of daa available during he design sage, namely he CAD model of he par, he maerial name, and he producion requiremens. This mehodology uses his daa o esimae he parameers of he runner sysem and an appropriaely sized molding machine. I hen uses hese esimaes o compue he machine seup ime and he cycle ime required for he injecion molding operaion. This is done by appropriaely absracing informaion available from he mold flow simulaion ools and analyical models ha are radiionally used during he manufacuring sage. These imes are hen muliplied by he power consumed by he appropriaely sized machine during each sage of he molding cycle o compue he esimaed energy consumpion per par. 1. INTRODUCTION Over he pas several decades, plasics have moved from small-scale applicaion in highly specialized niche markes, o a ubiquious presence in everyday consumer Arvind Ananhanarayanan Deparmen of Mechanical Engineering Universiy of Maryland College Park, Maryland Ram D. Sriram Manufacuring Sysems Inegraion Division Naional Insiue of Sandards and Technology Gaihersburg, MD producs. Plasics are popular engineering maerials because of heir versailiy, durabiliy, and relaively low cos. However, hey also presen significan environmenal and human healh challenges: hey are slow o break down in lands and oceans, heir processing consumes a large amoun of energy, and hey can release a number of subsances during usage and disposal which may have adverse effecs on humans and he environmen. One of he mos heavily used processes for creaing plasic pars is injecion molding. In his process, liquefied polymer is injeced a high pressure ino a mold caviy. The polymer akes he shape of he caviy, and is cooled eiher passively or acively using waer channels. The resuling par is hen ejeced from he mold caviy, and he molding machine is rese for he nex par. The main environmenal concerns associaed wih injecion molding are energy consumpion and wase generaion. During injecion molding, energy is consumed o mel, injec and pressurize he resin, open and close he mold, and pump waer for cooling. This energy consumpion has significan environmenal consequences. In he very counries wih he larges injecion molding indusries, elecrical energy is mosly produced hrough combusion of fossil fuels [1, 2]. The burning of fossil fuels for elecriciy generaion is he larges single anhropogenic source of he greenhouse gas emissions responsible for global warming [3]. Wase, in he form of he addiional polymer in sprues and runners, is also anoher significan environmenal concern. This wase is more prominen in injecion molds having cold runners. This is because he polymer in he runners in such molds is no par of he final par. This wase is ofen recycled by regrinding he 1

2 wase polymer ino pelles. This, in urn, increases he overall energy consumpion. I is herefore clear ha, o miigae he environmenal impac of such processes, here is a need for an accurae mehod for esimaing he energy consumpion, resource consumpion, wase and emissions ha resul from he plasic manufacuring. Furhermore, i is necessary o look beyond simply he impac of he injecion molding faciliy. Boh upsream and downsream impacs accrued during resource exracion, shipping, usage, and disposal should be considered as well. However, his paper does no aemp o perform he enire life cycle assessmen for plasic pars. Insead, our scope is limied o he energy consumed during he injecion molding operaion. Currenly mos injecion molded pars are opimized a he design sage wih respec o he cos and par qualiy. Once he design has been opimized for hese crieria, he mold for par producion is machined. This mold could be used for acively measuring he energy consumpion by connecing an energy meer o he injecion molding machine during producion. However, building a ypical producion-qualiy mold for energy esimaion alone is no economically viable [4]. In order for he energy esimaion o be beneficial, i is necessary for he designer o obain his informaion a he design sage, before he mold has been machined. The designer can hen use his informaion o opimize he design for energy consumpion. During he design sage, fully characerizing he manufacuring sage is exremely challenging as here are many differen facors and parameers which drive energy consumpion. These parameers are more han simply he par volume and maerial choice, which are ypically he sole basis on which energy consumpion is esimaed oday. In addiion o he volume, oher informaion from he geomery model of he par such as projeced area, par deph, and imum wall hickness has a significan effec on he energy consumpion. The sysem of runners ha carries he molen polymer from he injecion nozzle o various caviies in he mold also plays a major role in esimaing energy consumpion. In some cases, he volume of he runner sysem can be as large as, or larger han he volume of he par iself. Therefore, significan energy is expended o mel his addiional maerial. The size and arrangemen of he runners may also require a larger injecion molding machine. Differen injecion molding machines consume vasly differen amouns of energy, based on he size of heir clamping mechanisms, screw, heaer, and pumps. Producion requiremens also have an indirec conribuion o he energy consumpion. For example, producion in smaller baches requires ha he machine be warmed up and calibraed more ofen, hus requiring more energy each ime a bach is sared. Producion requiremens may also play a role in deermining he runner layou of he par, as well as he size of he machine ha will be used. Thus, he geomeric model of he par, he runner sysem for he mold, he size of he machine, and he producion requiremens inerac in a complex way o influence he per-par energy consumpion during injecion molding. Unforunaely, mos of his informaion is no available during he design sage. Typically, he available daa consiss of he CAD model of he par, he maerial o be used, and he producion volume. This informaion can be used o obain an accurae esimae of energy consumpion, bu i requires addiional simulaion ools such as Moldflow and discree even simulaion (DES), and careful applicaion of various analyical models. In addiion, non par-specific informaion, such as a daabase of runner layous, and a daabase of power consumpion profiles for various injecion molding machines are needed o make appropriae inferences abou new par designs. Much of his informaion is currenly eiher unavailable, or no compiled ino an easily accessible daabase. Therefore, appropriae emplaes mus be consruced for gahering and organizing his informaion in a sysemaic manner. In his paper, we propose a mehodology o esimae he per-par energy requiremen for injecion molded pars during he design sage. This mehodology begins by uilizing he informaion provided by he CAD model of he par and informaion on similar pars which have already been molded. From his informaion, he maerial parameers, and he producion volume, inferences are made o calculae he parameers of a surrogae runner sysem, a surrogae injecion molding machine, and he producion policy for manufacuring he par. From hese esimaed parameers, we compue he ime spen during each sage of seup and molding. This is done by appropriaely absracing informaion from he mold flow simulaion ools and analyical models ha are radiionally used during he design sage. Nex, informaion on he runner layou of similar pars, and he power consumpion profile of an appropriaely sized injecion molding machine is colleced. Finally, he oal energy consumpion in kilojoules per par is compued by muliplying he power consumed by he machine in each sage of molding, and hen muliplying i by he esimaed par-specific seup and cycle imes. 2. OVERVIEW OF EXISTING METHODS Currenly, several heurisics exis for assessing he environmenal and healh impac of a given produc, process, or sysem. One such mehod is known as Life Cycle Assessmen (LCA), and is defined in he ISO sandard. According o ISO 14040, LCA consiss of four sages: 1) goal and scope, 2) invenory, 3) assessmen, and 4) inerpreaion. In he goal and scope sage, he problem and is boundaries are defined. In he invenory sage, he maerials used, processes execued, and wase produced a each sage of he produc s life cycle are quanified. In he assessmen sage, values from he LCA are used o calculae, normalize, and weigh he impac of he produc in one or more caegories. Various assessmen mehodologies [5] have been developed which can be adaped wih LCA sofware such as GaBi [6] or SimaPro [7]. In he final sage, inerpreaion, he reviewer inerpres he resuls 2

3 of he assessmen, draws conclusions, and makes recommendaions. The goal and scope and inerpreaion sages require qualiaive and conex-specific judgemen, and hus inrinsically require a human hinker. Therefore, here is lile scope for improvemen in his sage from an engineering sandpoin. The assessmen sage is fairly well suppored by curren generaion LCA ools. Sophisicaed algorihms have been developed o ransform inpu daa such as greenhouse gas emissions, waer polluans, and raw maerials exraced from naure, ino measurable impacs on ecosysems, climae change, and human healh. Currenly, he weakes poin of LCA is he invenory sage, where he inpu daa is calculaed and abulaed. For injecion molded pars, a proper LCA requires ha he energy consumed during manufacuring be accouned for. Energy consumed a oher sages of he plasic life cycle such as peroleum refining, shipping, usage, and recycling mus also be considered, bu accouning for his daa will be considered in fuure work. Curren LCA models of energy consumpion for he injecion-molding process use an allocaion scheme, based on specific energy consumpion (SEC) [8]. SEC is defined as he amoun of energy used by a specific process for a uni quaniy of maerial. The mass of he par, which can be obained from a CAD model, is muliplied by he injecionmolding SEC for he given maerial, which can be found in an LCA daabase. From his calculaion, an esimae of energy consumpion is obained. This process is shown in FIGURE 1. Larger machines require more hermal energy o mainain he polymer emperaure, and more power o move he heavier injecion and clamping mechanisms. These generalizaions lead o wildly inaccurae energy esimaes. In addiion, he allocaion scheme based on SEC and par mass do no accoun for he influence of par geomery and cycle ime. Pars having he same volume and herefore he same mass, bu differen geomery can have significanly differen cycle imes and herefore require differen amouns of energy o manufacure. For example, le us consider he wo pars shown in FIGURE 2. Boh pars are made using he same maerial and have he same volume and mass. However, he imum wall hickness of he smaller, more compac par (a) is wice ha of he larger, hinner par (b). The cooling ime for an injecion molded par is proporional o he square of he imum wall hickness [4]. Therefore he cooling ime for he cup in FIGURE 2 (a) will be approximaely 4 imes ha of he cup in FIGURE 2 (b). During he cooling ime, he machine coninues o idle and consume energy. Therefore increased cooling ime, along wih increasing he cycle ime of he operaion, also resuls in increased energy consumpion. Sudies by Guowski [9] and Krishnan [10, 11] show ha he energy consumed by overhead operaions such as mainaining he polymer mel and he mold emperaure along wih pumping fluids and coolans, can be more han he energy used during each producion run. Thick pars may especially require acive cooling, which requires use of even more energy o supply coolans. CAD Geomery Model Maerial Type Inpus Par Mass Average Energy per kg Muliply LCA Daabase (a) FIGURE 2: TWO DIFFERENT PARTS WITH EQUAL VOLUME BUT DIFFERENT WALL THICKNESSES AND COOLING TIMES. PART (A) HAS A WALL THICKNESS OF 0.05 IN., WHILE PART (B) HAS A WALL THICKNESS OF IN. BOTH PARTS HAVE A VOLUME OF 3.34 IN 3. (b) Energy Consumpion (Per Par) Oupu FIGURE 1: CURRENT METHOD USED TO INVENTORY ENERGY CONSUMPTION FOR INJECTION MOLDING. Unforunaely, he available LCA daabases only provide an average over he range of machines used in he indusry. This is inadequae because properies of he specific machine used dramaically influence energy consumpion. Guowski and Krishnan [9-11] have shown ha machines wih a ypically higher hroughpu end o consume less energy per par. This can be explained by he influence ha cycle ime has on energy consumpion as described above. Since he baseline idling energy is relaively consan, a machine having lower ypical cycle imes allocaes less idling energy per par. To accoun for he effecs of baseline idling energy, Guowski divides he specific energy consumpion ino wo componens: one componen represens he energy used while 3

4 he machine is idling, and he second componen represens he addiional energy used o process each uni of maerial. However, his mehod sill does no accoun for he variaions in power consumpion a differen sages of he molding cycle. A 2007 sudy [12] invesigaing he effecs of conformal cooling channels on energy consumpion showed ha a 40% reducion in cycle ime for he same par on he same machine resuls in only a 20% reducion in energy consumpion. This suggess ha he porion of he cycle ha was shorened consumed power a a rae lower han he average for he enire molding cycle. Therefore, an approach ha accouns for a specific par geomery and machine a each sage of he molding cycle could help o achieve a more accurae esimae of energy consumpion. 3. PROBLEM STATEMENT The goal of our paper is o develop a mehodology for esimaing he energy required o manufacure a par during he design sage. This will enable designers o make changes o he design ha minimize he overall energy consumpion. Unforunaely, as menioned earlier, only limied informaion is available o esimae molding energy consumpion a he design sage. Typically, informaion is available from hree sources: he design eam, he maerial supplier, and indusry daabases. From hese sources, he following se of daa can be obained which comprises he inpus o our mehodology. Informaion available from design eam (1) A geomeric model of he par. This consiss of a model creaed in a common CAD package such as AuoCAD, ProEngineer, or SolidWorks. This model can be used for deermining volume, par deph, imum wall hickness, and projeced area. (2) Maerial. The precise maerial mus be known, including he maerial manufacurer, resin ype, and er ype and concenraion. (3) Par delivery schedule. To predic he energy consumed during seup and mainenance of he injecion molding machine, i is necessary o deermine how ofen seups and mainenance will be performed. This depends on how ofen he machine is run o produce a bach of pars, which we will call he bach period. The bach period depends primarily on he delivery schedule required by he cusomer, bu can be opimized using warehouse sorage o minimize cos. To deermine he opimal bach period, we mus know he delivery schedule, which consiss of he following pieces of informaion: a. Delivery volume. This is he number of pars ha mus be delivered a a ime o he cusomer. b. Delivery period. This is he inerval beween deliveries of pars o he cusomer, measured in days. c. Producion volume. This is he oal number of pars ha he cusomer needs. We assume ha his is a whole muliple of he delivery volume. Maerial Informaion Daa on molding parameers for he maerial can be procured from maerial daashees provided by suppliers. For he seleced maerial, he following informaion is required: (1) Densiy. This is he densiy of he molded maerial, in g/cm 3. (2) Specific hea capaciy. This is he energy required o hea one gram of he maerial by one degree Celsius. Unis are J/g- C. (3) Recommended injecion pressure. This is he imum pressure a he nozzle during he ing phase. Unis are N/cm 2. (4) Recommended polymer injecion emperaure. This is he emperaure a which he polymer is injeced ino he caviy. Unis are degrees Celsius. (5) Recommended mold emperaure. This is he recommended emperaure o which he mold should be heaed prior o injecion. Unis are degrees Celsius. (6) Recommended ejecion emperaure. This is he recommended emperaure o which he molded par should be cooled prior o ejecion from he mold. Unis are degrees Celsius. Daabase Consrucion In addiion, we can use informaion from indusry daabases ha mos closely maches our anicipaed manufacuring scenario. For he purposes of his paper, we will consruc our own preliminary daabases which will be expanded in he fuure. The informaion in hese daabases consiss of he following: (1) Machine daabase. This daabase conains comprehensive informaion on a se of injecion molding machines of varying sizes. For each machine, he following informaion mus be available: a. Clamping force. This is he imum force ha he clamping mechanism is able o apply o he exerior of he mold o couner he pressure exered by he flow of polymer ino he mold caviy. Unis for his are newons (N). b. Sho size. This is he larges volume of polymer ha he machine can deliver o he mold caviy in a single cycle. This has unis of cm 3. c. Sroke lengh. This is he imum possible displacemen of he mold from he closed sae. This has unis of cenimeers (cm). d. Maximum flow rae. This is he imum rae a which he machine can deliver maerial hrough he injecion nozzle. Unis for his are cm 3 /s. e. profile. This is a se of daa which provides he average amoun of energy used by he machine per 4

5 uni ime, during each phase of he machine cycle. In addiion o he power required during ing, cooling, and reseing, his profile should also include he average power used during seup, mainenance, and oher evens during which he machine is idling and hus consuming energy. f. Dry cycle ime. This is he ime required for he machine o complee an injecion cycle when injecing a sandard caviy wih air, insead of molen plasic. Unis for his are seconds. g. Average seup ime. This is he average ime required o seup he machine. Unis are measured in seconds. h. Average number of calibraion pars. This is he average number of pars ha are discarded during calibraion of he machine. (2) Runner sysem daabase. This daabase mus conain many pars wih differen geomeries, qualiy requiremens, number of caviies, and runner sysems. The runner sysem for a new par can be inferred from he runner sysem of previously manufacured pars wih similar geomeries, qualiy requiremens, and number of caviies. Based on he above described informaion, we seek o esimae he per-par energy consumpion for a molded par. This includes he energy used during he molding cycle, as well as he energy used during seup and calibraion, amorized over he oal number of pars in he bach. We assume ha we are dealing wih very high producion volumes, and hus he energy consumpion of making he mold would be very small in comparison and can be ignored. Furhermore, we ignore he energy consumpion for machine mainenance in his paper. 4. OVERVIEW OF APPROACH To develop an accurae mehod for esimaing energy consumpion for injecion molded pars, we have formulaed an algorihm consising of five seps. These seps are: (1) Deermine a surrogae runner arrangemen, and is volume, for he mold. (2) Approximae he parameers of he machine ha will be used based on he producion requiremens. (3) Esimae various componens of he cycle ime for molding a par. (4) Esimae he number of seup operaions based on he delivery schedule. (5) Muliply hese imes by he appropriae average power used in each sage by he seleced machine, and sum o ge he oal energy consumpion. This approach is summarized in FIGURE 3. Firs, we analyze he CAD model of our par o deermine he mold caviy volume. In addiion o he volume of he par, we mus also consider he volume of he runner sysem and sprue. In some pars, especially pars a he small scale, he runner sysem can be much larger han he par. Hence i is imporan o carefully selec he runner layou for esimaing he projeced volume of he mold caviy. 5. SELECTION OF RUNNER LAYOUT To arrive a a good esimae of he per-par energy consumpion, we mus be able o accuraely predic how he mold caviies and runner sysem will be laid ou when he par goes ino producion. Selecion of he appropriae runner layou is one of he mos challenging problems encounered by mold designers [13]. The problem involves concurren opimizaion for 1) ensuring complee ing of he caviies, 2) minimizing he raio of runner volume o par volume o minimize maerial wase, and 3) mainaining par qualiy by ensuring ha par qualiy parameers such as shrinkage, warpage, residual sresses, shear variaions ec. are wihin he specified olerances. Inpus CAD Geomery Model Par Reposiory CAD File Maerial Runners Machine Profile Daabase Maerial Properies Delivery Schedule Case-Based Comparison Par and Surrogae Runner Arrangemen MoldFlow Molding Simulaion Profile Discree Even Simulaion / Analyical Model Oupu Caviy Volume and Area Esimaion of Machine Parameers Cycle Times Seup Times Par Deph Energy Consumpion (Per Par) FIGURE 3: GENERAL APPROACH FOR ESTIMATING PER-PART ENERGY CONSUMPTION. 5

6 Considering he above opimizaion parameers, manufacurers are always looking o imize he number of caviies in each mold. This sraegy increases produciviy by reducing he cycle ime per par while mainaining he cycle ime for each injecion. However muliple caviy molds make producion of idenical pars challenging. This is because here may be discrepancies in he pars in each caviy of he mold depending on he layou of he runner and each caviy in he mold. This discrepancy is caused by several facors as illusraed in FIGURE 4 [14]. Several researchers have sudied he effecs of discrepancies based on various parameers such as geomeric balancing [15], pressure and emperaure [16], shrinkage [17], weld-line posiioning [18], and oal ime [19]. These discrepancies become even more pronounced as he caviies move furher away from he cener of he mold. This is because he mold deformaion during he packing phase is a a imum near he cener of he mold [13]. Hence as he caviies are moved furher away from he cener, here is significan difference in he pressures seen in each caviy. This in urn influences he par qualiy. Hence he pars produced in each caviy are no idenical. Researchers have argued ha his discrepancy is more pronounced in caviies wih eigh or more caviies per mold [13]. Hence for he sake of his effor, we will resric ourselves o molds having up o four caviies. FIGURE 4: CRITERIA FOR MOLDABILITY EVALUATION [14]. FIGURE 5 illusraes eigh differen sprue/runner layous for four-caviy molds. These layous are commonly used layous which use fishbone and ladder layous. The mos appropriae runner layou is seleced based on he criical qualiy merics such as shrinkage, shear level, par densiy, mold machining consrains ec. while opimizing for he cycle ime and he overall runner volume. The geomery of he mold and he sprue locaion also plays a significan role in he selecion of he mos appropriae runner layou. Considering he complex naure of his problem, manufacurers currenly selec he mos appropriae runner/sprue layou based on heir prior experience. Hence for he purpose of oal energy esimaion which is he focus of his paper, we will choose he runner design based on our previous injecion molding experience. As par of he fuure work, we will develop a performance heurisic based mehod o auomae he selecion of he opimum runner/sprue layou for any given par which is envisaged o be manufacured using injecion molding. In his paper, we will use he par shown in Error! Reference source no found. as a running example. This is a generic housing for an elecronic device, and is mean o represen he ypical shapes and feaures found in plasic housings. We have seleced Hival ABS HG6 Naural, produced by Ashland Disribuion [20] as he maerial for his par. ABS is a common and widely used plasic for elecronic device housings. For our delivery schedule, we assume ha he cusomer requires a shipmen of 50,000 pars every wo weeks, for a oal producion volume of 2 million pars. For selecing he runner design for his par we idenified a similar par from our injecion molding par library. This par uses a four-caviy mold wih he runner design illusraed in FIGURE 7. This layou provided for 1) geomeric balancing for ing, 2) equal caviy disance from mold cener and 3) minimum volume of he runner. Hence, owing o par similariy, we used he same runner design for esimaing he energy consumpion for molding he example par shown in Error! Reference source no found.. This runner design is illusraed in FIGURE 8. We compued he minimum allowable runner size based on ing simulaions performed using Moldflow [21]. Finally, we seleced he runner diameer based on he ooling resricions for machining he mold. Once we seleced he runner/sprue layou and he oal number of caviies in he mold, we could compue he projeced area of he runner sysem and he runner volume. This informaion is hen used for selecing he machine for compleing he injecion molding operaion. 6. SELECTION OF MACHINE The nex sep is o esimae he size of he injecion molding machine required o mold he par. Machine size is primarily driven by he clamping force required o hold he mold closed during he injecion cycle, he sho size required by he volume of he par and runners, and he sroke lengh required o clear he imum deph of he par during par ejecion [4]. The par volume and imum deph of he par can be deermined from he geomeric model. The required clamping force can hen be deermined from he relaionship beween he imum caviy pressure and he projeced area of he caviy. The imum pressure in he mold can be deermined using Moldflow, given he prediced mold design from he firs sep and he recommended injecion pressure. We hen assume ha he manufacurer will use he cheapes machine which can provide he necessary clamping force, sho size, and sroke lengh. The required sho size is equal o he volume of he par, plus he volume of he runners and sprue. This oal volume can be deermined using Moldflow. The sroke lengh L s is ypically esimaed by a linear relaionship wih he imum deph of he par. A machine which mees hese crieria can be looked up in machine daabase [22]. For his sudy, we have buil a small daabase of machines based on he lis given in [4]. 6

7 (a) One-sided Ladder (b) Two-sided Ladder (c) Geomerically balanced wosided Ladder (d) Geomerically balanced, cenered wo-sided Ladder FIGURE 7: RUNNER DESIGN FOR INJECTION MOLDING OF PART IN REPOSITORY AT THE ADVANCED MANUFACTURING LAB. (e) One-sided Fishbone (f) Geomerically balanced one-sided Fishbone FIGURE 8: RUNNER DESIGN FOR ENERGY ESTIMATION STUDY PART. (g) Geomerically balanced wo-sided Fishbone (h) Geomerically balanced, cenered wo-sided Fishbone FIGURE 5: DIFFERENT SPRUE AND RUNNER LAYOUT FOR FOUR-CAVITY MOLDS. THE RED CIRCLES REPRESENT THE SPRUE, AND EACH YELLOW RECTANGLE REPRESENTS A SINGLE MOLD CAVITY. Thus, machine selecion consiss of he following algorihm: Inpus: V caviy volume of caviy (sho size), cm 3 P imum caviy pressure, (N/cm 2 ) A caviy projeced area of mold caviy parallel o paring line, cm 2 L sroke imum required sroke lengh for machine, cm D imum par deph, cm n caviies number of mold caviies (pars per sho) FIGURE 6: CAD MODEL AND MANUFACTURED PRODUCT FOR AN EXAMPLE PART REPRESENTING A GENERIC ELECTRONICS HOUSING. Oupu: The seleced machine M for he par. Algorihm selecmachine: Compue F and L. clamp sroke o F = P A (1) clamp caviy 7

8 o L = 2D+ 5 (2) sroke Selec a machine M from he daabase of machines for which o he imum clamping force Fclamp AND o he imum sroke lengh L L AND sroke F clamp sroke o he imum sho volume V Vcaviy AND o he machine rae minimized. c machine is greaer han is greaer han is greaer han, in dollars per hour, is The geomeric aribues for a four-caviy mold for our example par (shown in FIGURE 8) are as follows: Vcaviy = ncaviiesvpar + Vrunners (3) V A caviy caviy D = h = cm cm = cm = cm cm = cm The imum pressure in he caviy is esimaed as 50% of he recommended injecion pressure for he seleced maerial [4]. For Hival ABS HG6 Naural, his gives us he imum caviy pressure as: P = 5 kn/cm 2 This esimaed value is verified using MoldFlow simulaions of he caviy ing sage wih he seleced machine and maerial parameers. If a discrepancy is found, hen his value is modified using MoldFlow simulaion daa. Given hese values, we can compue he required clamping force and sroke lengh o successfully mold he par. We can hen selec he machine from our daabase ha minimizes cos while meeing he consrains of sho size, clamping force, and sroke lengh. In TABLE 1 we compare he resuls for our par wih he specificaions of our seleced machine[23]. TABLE 1: COMPARISON OF ESTIMATED CLAMPING FORCE, SHOT SIZE, AND STROKE LENGTH FOR THE PART ALONG WITH MAXIMUM POSSIBLE VALUES FOR THE CLOSEST-MATCH INJECTION MOLDING MACHINE. Parameer Experimenal Par 5.5kW Machine F 104 kn 300 kn clamp 3 V caviy cm 3 34 cm L cm 20 cm sroke 7. ESTIMATION OF CYCLE TIMES Load Hopper Producion energy for inpu maerials Mainain Mainenance ime Average mainenance power Flush Flush ime (DES) Average flush power Mainenance Ejec Ejecion ime (par) ejecion Reseing Open Opening ime (par and machine) opening Cool Cooling ime (par) cooling Clamping power Acive cooling Insall Mold Energy cos of mold Warmup Warmup ime (machine) warmup Calibrae Producion energy of scrapped maerial Toal cycle energy Inser and Close Closing ime (par and machine) closing Injec Injecion ime (par) injecion Ho runner power Pack Packing ime (par) packing Cooling Seup FIGURE 9: STATE-TRANSITION DIAGRAM OF A TYPICAL INJECTION-MOLDING OPERATION. Once he machine has been seleced, he cycle ime for he par can be esimaed. The molding cycle can be broken down ino hree sages: injecion, packing and cooling, and rese. These sages, as well as heir sub-sages and oher auxiliary sages in a ypical injecion molding operaion, are shown in he sae ransiion diagram in FIGURE 9. During he injecion sage, he pressure a he injecion nozzle is gradually increased. This is done o mainain a consan volumeric flow rae, as he mel cools and solidifies. The esimaed ime for he mold caviy can be derived based on he imum flow rae [4]. This relaionship is as follows: 2V caviy = (4) Q where Q is he imum flow rae of polymer from he nozzle. 8

9 Nex, he pressure is held and hen gradually dropped as he par cools and conracs in he mold. We assume ha acive cooling is no used. Using he firs erm of he Carslaw and Jaeger soluion [24], he cooling ime in seconds can be esimaed from he imum wall hickness of he par and he processing parameers and hermal diffusiviy of he polymer. The imum wall hickness can be deermined from he par model, and he processing parameers can be found from he maerial daashee provided by he supplier. Given: h Ti Tm Tx α imum wall hickness of par polymer injecion emperaure recommended mold emperaure recommended par ejecion emperaure hermal diffusiviy of maerial We can esimae he cooling ime as: ( T T ) i m ( T T ) x m 2 h 4 = ln cool 2 πα π The hermal diffusiviy can be compued from he specific hea, hermal conduciviy, and densiy of he maerial as: k α = (6) ρ c resin resin where k is he hermal conduciviy of he maerial. Finally, afer ejecion of he par, he mold is prepared for he nex cycle. This ime is esimaed by applying an overhead o he dry cycle ime for he machine. The dry cycle ime is a performance meric ha indicaes he ime for he machine o perform he acions necessary o manufacure a par, wihou he par acually being produced. The overhead is derived from he par deph (D) and sroke lengh (L sroke ). Adding a 1-second dwell ejecion, he rese ime is calculaed as: rese = L sroke L sroke where d is he dry cycle ime for he machine. d For our example, we use he machine ha we seleced in he previous secion. This is he leas expensive machine capable of producing our par. The machine parameers are given in TABLE 2. The maerial properies for Hival ABS HG6 Naural are provided in TABLE 3. TABLE 2: TABLE OF PARAMETERS FOR THE SELECTED INJECTION MOLDING MACHINE. Parameer 5.5 kw Machine 3 Q 55 cm /s d 1.7 s c 28 $US/hr machine (5) (7) TABLE 3: TABLE OF PARAMETERS FOR THE SELECTED MATERIAL. Param. Hival ABS c 1.96 J/g C T resin i ρ 3 resin 1.04 g/cm T m 2 α cm /s T x Param. Hival ABS 240 C 50 C 109 C Given hese values, we can compue he cycle imes as follows: cool rese = s = s = s 8. ESTIMATION OF SETUP OPERATIONS For our applicaion, we seek o deermine he amoun of energy consumed during machine seup, per par. This is done by deermining he oal energy used during he machine seup before he sar of he producion. Seup processes include seps such as warming up he machine, insalling he mold, and calibraing he machine. The injecion molding machine consumes significan amoun of energy during warmup, and hen coninues o consume energy as i idles during mold insallaion. Before sar of producion, he injecion molding process needs o be sabilized. This is done o esablish process equilibrium o ensure complee ing of he par, avoid jeing ec. Manufacurers ypically rejec he firs few ens of pars before beginning he producion. We herefore include he energy consumed during his sep as par of he machine calibraion. To deermine he oal energy used during seup processes, we mus firs deermine how ofen he machine mus be se up during he producion schedule of he enire producion volume. Typically, he enire producion volume will no be compleed in a single producion run. Typical injecion molded pars are produced based on he producion requiremen and he delivery schedule. The cusomer specified delivery schedule involves a reques for a cerain number of pars a regular ime inervals. Thus, o save on he invenory cos before delivery o he cusomer, he manufacurer makes pars in baches. The bach size should be larger han he number of pars delivery requiremen a each ime inerval. Therefore, any remaining pars mus be sored a he expense of he manufacurer unil he nex delivery. However, larger bach sizes require fewer seups. Therefore, here is a radeoff beween he seup cos and he invenory cos. FIGURE 10 shows he relaionship beween he delivery schedule and he producion schedule over he enire producion volume. The manufacurer produces a cerain number of pars, and delivers o he cusomer a regular 9

10 inervals. During his ime, undelivered pars remain in sorage. When he pars in sorage have been depleed, he manufacurer makes a new bach of pars, and coninues o ship hem ou according o he cusomer s delivery schedule. We assume a regular delivery inerval for our purposes. N=Tn/k Pars in sorage 2n n T 0 k 2k T T+k T+2k 2T manufacure deliver deliver deliver manufacure deliver deliver deliver ime FIGURE 10: GRAPH SHOWING DELIVERY SCHEDULE AND PRODUCTION SCHEDULE IN TERMS OF PARTS IN STORAGE VERSUS TIME. This radeoff can be formulaed as a single variable opimizaion problem. The soluion o his problem gives us he opimal number of seup operaions which minimize he cos o he manufacurer over he enire producion volume. For his problem, we assume ha he bach producion period is much larger han he delivery period, and so lead ime can be ignored. Furhermore, we assume ha he manufacurer mus pay for a consan amoun of sorage; even as he manufacurer s invenory is depleed, hey mus coninue o pay for he enire space needed o accommodae a bach of pars. Given: N X n k c c T q q seup sore seups sore We formulae our opimizaion problem as follows. bach producion volume oal producion volume delivery volume delivery period (days) cos o se up one bach cos o sore one uni per day manufacuring period (days) = Xk / Tn number of seup operaions = XT sorage quaniy in iem-days where T is our design variable, we can minimize he oal cos CT ( ) as follows: min CT ( ) = q c + q c T s.. seups seup sore sore T > k > 0 Making subsiuions for q and q, we ge seups sore (8) Xk C( T ) = c + XTc (9) seup sore Tn Using KKT condiions, we arrive a he following soluion: T kc seup = (10) nc sore Thus we can deermine he opimal number of seup operaions which minimize cos as: Xk q = (11) seups Tn For our example, we assume he oal producion volume, delivery volume, and delivery period as: X = n = k = 14 days Furhermore, we assume ha he cos of a single seup operaion is proporional o he seup ime and he hourly machine rae; i.e.: c = c (12) seup c = seup machine seup 56 $US To deermine he sorage cos, we used he average rae for public sorage as adverised by Public Sorage [25]. A ypical 10 x10 x8 sorage space in he College Park area coss approximaely 150 $US per monh. Assuming a 25% packing raio, his is equivalen o: c = sore $US per 3 cm per day. Thus, compuing he opimal bach period gives us: T 133 days and herefore: q seups 4 In oher words, we will make 500,000 pars a a ime. 9. ESTIMATION OF TOTAL ENERGY CONSUMPTION The energy used during ing, cooling, and reseing can be deermined from he cycle imes and he power profile of he machine. We have already deermined he cycle ime of he par, including he imes required o he mold, cool he par, and rese he machine. Guowski [9] and Krishnan [10, 11] have published energy consumpion profiles for various injecion molding machines. We assume ha energy consumpion per uni of ime on a given machine is consan for a given par of he cycle. Therefore, we can look up he power required, in was, for he machine during each sage of he injecion molding cycle. Given: 10

11 cool rese avg. power used o he mold, kw avg. power used o cool he par, kw avg. power used o rese he machine, kw We can deermine in kilojoules he energy used during ing, E, he energy used during cooling, E cool o rese he machine, E E E E as: rese, and he energy used = (13) n caviies cool cool = (14) cool n caviies rese rese = (15) rese n caviies To deermine he average powers shown in TABLE 4, we measured he power consumpion on a 2.9 kw Milacron Babyplas injecion molding machine available in our lab. This was done by connecing a clamp-on mulimeer o he hreephase power supply of he Milacron Babyplas. We hen warmed up he machine, and molded several sample pars. We recorded he average power consumpion using an Exech meer during warmup and during he hree major sages of molding. These measuremens are shown in TABLE 4. We calculaed he expeced power consumpion for he seleced machine by scaling he measured powers for he Milacron Babyplas injecion molding machine by he raio of is driving power of 2.9 kw, o he driving power of he 5.5 kw machine. In he fuure, we plan o direcly insrumen a wide variey of injecion molding machines o obain a more accurae scaling law for average power consumpion. TABLE 4: AVERAGE POWER CONSUMPTION OF EACH STAGE OF MOLDING CYCLE FOR SELECTED MACHINE. Parameer Babyplas 5.5 kw Machine seup kw kw 1.6 kw kw cool kw kw rese kw kw Using hese values, we find a resul of: E E E cool rese = kj = kj = kj The oher quaniies we mus calculae are he amouns of energy used during seup and calibraing he machine. Assuming ha we also know he average power in kilowas used by he machine during seup,, and he average seup ime required o seup he machine in seconds, seup, we can deermine he energy used during a seup operaion, muliply i by he number of seup operaions, and divide by he oal producion volume. Thus, we allocae he oal seup energy o arrive a he per-par seup energy as: qseups E = seup seup seup (16) X For our operaion, we assume ha he warm up ime for each machine se up is wo hours, or 7200 seconds. This gives us he seup energy of: E = seup kj Nex, we allocae he energy used o mold each par during calibraion, o he oal producion volume. Assuming ha x pars are made and discarded during he calibraion calibrae process, we arrive a he per-par calibraion energy as: q x seups calibrae E = calibrae ( E + E + E cool rese ) q x + X seups calibrae For our operaion, we assume: x = calibrae 250 pars Thus, we can compue E as follows: calibrae ( ) / 2001 E = E + E + E calibrae cool rese E = calibrae kj (17) Adding up hese energies, we ge he oal energy consumed per good par produced as: E = E + E + E + E + E (18) seup calibrae cool rese The esimaed oal energy consumpion for our par is: E = kj I is clear ha cooling and reseing dominae he energy consumpion for our example par. Alhough he ing sage uses he mos power, ing happens very quickly and hus does no dominae he energy used. Seup and calibraion have also been shown o have small, bu measurable conribuions o energy consumpion. A his poin, we have only esimaed he energy consumed during injecion molding. For a complee life cycle analysis, we would need o deermine he energy consumed during producion of he polymer maerials, he energy used for ransporaion during he various sages in he supply chain, energy associaed wih he par s usage, and energy consumed during disposal. This work focuses only on manufacuring, and so he oher sages of he produc life cycle were no addressed. 11

12 10. CONCLUSION This paper is he firs aemp a developing a mehodology for obaining an accurae esimae of he oal energy consumpion for producion of injecion molded pars by incorporaing he differen aspecs of he molding cycle. This mehodology can be applied a he design sage, and hus allows he designer o make energy-conscienious decisions before he par goes ino producion. We presen a mehod for esimaing he energy consumpion by 1) selecing he runner layou based on par similariies, 2) performing physics based simulaions on he specific par o firs selec he machine for injecion molding and hen esimae he cycle ime for producion, 3) compuing he producion volume based on he delivery schedule, he energy overheads (machine seup energy, calibraion energy ec.) for each producion run and he invenory cos, and 4) esimaing he oal energy usage using by performing physical experimens o measure he power profiles on an injecion molding machine. Finally, muliplying hese imes wih he average power consumed during each sage of he process, and adding up he resuls, gives us he oal perpar energy consumpion. In fuure work, we plan o es he validiy of our model by using oher pars on differen machines and measuring he acual energy consumpion on hose machines. We hope ha a more accurae model of energy consumpion for molding plasic pars will help designers make beer, more environmenally-conscienious decisions during he design process, raher han waiing unil manufacuring has already begun o perform energy consumpion audis. Acknowledgemens: This research is suppored in par by he Naional Insiue of Sandards and Technology s (NIST) Manufacuring Sysem Inegraion Division. 11. REFERENCES 1. Plasemar. Chinese injecion molding indusry is poised for a good growh. 2009; Available from: hp:// -molding-indusry-china-poised-for-goodgrowh%20.asp. 2. EIA Inernaional Energy Annual , US Energy Informaion Adminisraion. 3. EDGAR 3.2 Fas Track , Neherlands Environmenal Assessmen Agency. 4. Boohroyd, G., P. Dewhurs, and W. Knigh, Produc Design for Manufacure and Assembly. 2 ed. 2002, New York: Marcel Dekker. 5. Jollie, O., e al., IMPACT 2002+: A New Life Cycle Impac Assessmen Mehodology. INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT, (6): p PE_Inernaional, GaBi : Leinfelden- Echerdingen, Germany 7. PRé_Consulans, SimaPro : Amersfoor, The Neherlands. 8. Thiriez, A. and T. Guowski, An Environmenal Analysis of Injecion Molding, in ISEE Guowski, T., J. Dahmus, and A. Thiriez, Elecrical Energy Requiremens for Manufacuring Processes, in 13 h CIRP Inernaional Conference on Life Cycle Engineering. 2006: Leuven, Belgium. 10. Krishnan, S.S., e al., Machine Level Energy Efficiency Analysis in Discree Manufacuring for a Susainable Energy Infrasrucure, in Inernaional Conference on Infrasrucure Sysems : Chennai, India. 11. Krishnan, S.S., e al., Susainabiliy Analysis and Energy fooprin based Design in he Produc Lifecycle, in Indo-US Workshop on Designing Susainable Producs, Services and Manufacuring Sysems,. 2009: Bangalore, India. 12. Morrow, W.R., e al., Environmenal aspecs of laserbased and convenional ool and die manufacuring. Journal of Cleaner Producion, : p Beaumon, J.P., Runner and Gaing Design Handbook: Tools for Successful Injecion Molding. 2004: Hanser Gardner Publicaions 14. Cheng, J., e al., Opimizaion of injecion mold based on fuzzy moldabiliy evaluaion. Journal of Maerials Processing Technology, (1-3): p Zhai, M., Y. Lam, and C. Au, Runner sizing in muliple caviy injecion mould by non-dominaed soring geneic algorihm. Engineering wih Compuers, (3): p Li, C.S. and Y.K. Shen, Opimum design of runner sysem balancing in injecion molding. Inernaional Communicaions in Hea and Mass Transfer, (2): p Alam, K. and M.R. Kamal, A robus opimizaion of injecion molding runner balancing. Compuers & Chemical Engineering, (9): p Zhai, M., Y. Lam, and C. Au, Runner sizing and weld line posiioning for plasics injecion moulding wih muliple gaes. Engineering wih Compuers, (3): p Lam, Y.C. and L.W. Seow, Caviy balance for plasic injecion molding. Polymer Engineering & Science, (6): p Ashland. Ashland Disribuion. 2010; Available from: Moldflow, Moldflow Plasics Insigh : Framingham, Massachuses. 22. Cusompar.ne: Free Online Manufacuring Cos Esimaion and Educaion Resource. 2008; Available from: hp:// 23. Babyplas, Babyplas Micro Injecion Molding Machines Carslaw, H.S. and J.C. Jaeger, Conducion of Hea in Solids. 1986, Oxford: Clarendon Press. 25. PS. Public Sorage. 2010; Available from: 12

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