AN INTELLIGENT MODEL FOR SALES AND INVENTORY MANAGEMENT

AN INTELLIGENT MODEL FOR SALES AND INVENTORY MANAGEMENT SYLVANUS O. ANIGBOGU, Ph.D. Associate Professor of Computer Sciece Departmet of Computer Sciece, Namdi Azikiwe Uiversity, Awka, Aambra State, 420001, Nigeria draigbogu@yahoo.com OLADIPO ONAOLAPO FRANCISCA, Ph.D. Departmet of Computer Sciece, Namdi Azikiwe Uiversity, Awka, Aambra State, 420001,Nigeria oaolamipo@yahoo.com KARIM USMAN, M.Sc. System Aalyst Departmet of Mathematics ad Computer Sciece Beue State Uiversity, Makurdi, Beue State, Nigeria www.karimkomputig.com, usmak4real@yahoo.co.uk ABSTRACT This work ivolved developig a itelliget model for sales ad ivetory maagemet aimed at bridgig the substatial gap betwee the theory ad the practice of ivetory maagemet. The system developed has the capability of providig automatic demad ad lead time patter idetificatio for ivetory maagemet. The itelliget ivetory model was formulated usig the cocept of fuzzy logic. The idetified patters ad the formulated model were traslated ito a rule based package developed with Java 2 Eterprise Editio (J2EE). The developed system ca work perfectly with ay small scale ad medium eterprise, but NOBIS super market (a reputable super market withi Makurdi metropolis, Beue State of Nigeria) was used to test ru the workig priciple of the system. The multi-brachig ature of the system ad its cliet server relatioship eve made it deployable for maufacturig ad airlie idustries aroud the globe. Keywords Ivetory cotrol, Rule-based system, Patter idetificatio, Fuzzy logic, J2EE 1.0 Itroductio Ivetory is the stock of some kid of physical commodity while ivetory maagemet is the determiatio of optimal procedures for procurig stocks of commodities to meet future demad. [1] Ivetory ca also be see as a firm s totality of stocks of various kids. Ivetory maagemet therefore takes care of aticipated demad, bulk purchase, absorbig wastages ad over orderig associated with ivetory. [2] Ivetory ca also be see as the quatity of product that a merchadisig firm has available to sell at ay give time. Ivetory maagemet system agai, moitors the quatity of each product available for sale ad help to esure that proper stock levels are maitaied. [3] Ivetory does ot ecessarily refer exclusively to physical merchadise or to goods available for immediate delivery. I airlie passeger reservatio systems, for istace, ivetory correspods to the umber of seats available o flights; i the registratio system at a typical uiversity or college; ivetory correspods to the opeigs available i each class. ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 785

This work focused o the mutual impact of treds i ivetory maagemet ad artificial itelliget techology. It is observed that, o oe had, the eed for sales ad ivetory maagemet is growig, while o the other, the possibilities of artificial itelligece ad software developmet beig the itegral part of ivetory are also growig. The motivatig factor behid this work is that sales ad ivetory maagemet ca be ehaced with the help of computer packages modeled with artificial itelligece. A major challege is to discover the potetial syergy betwee the busiess tred ad artificial itelligece tred. The problem of the maufacturer ad the retailer ca be take as a paradigm. For istace, i order to sell a item, the retailer or maufacturer must maitai a stock of that item to meet the demad for it. As his stock is depleted, the retailer or maufacturer will reorder or produce respectively more quatity so that the demad for the items by the customers ca be maitaied. Agai, it is also ecessary that some quatity should be stored so that the retailer or maufacturer does ot get out of stock. Ad such beig the ature of a ivetory, it follows that ivetory maagemet must deal with the logic which should uderlie this procedure. Apart from dealig with the logic, it also has to deal with some costs that are associated with ivetory which iclude orderig costs (i.e. cost of repleishmet ad fresh orders), holdig cost ad stock out costs. Hece, this work sought to address the problem of whe to order, what quatity to order i order to maximize profit ad miimize the risk of gettig out of stock. The key factor here ivolved developig a itelliget package to compute the optimum stock to order at a particular poit i time, ad to also moitor the level of stock so that whe the level falls below the predetermied level (predetermied level is itelligetly automatically determied by the system usig fuzzy logic model). I other words, the system automatically gives out sigals i the form of flashes or alerts or eve short message service (SMS) to otify the stock keeper or maufacturer to order or produce more materials or goods as the eed arises. Ivetory maagemet is a complex problem area owig to the diversity of real life situatios. Successful ivetory maagemet requires sophisticated methods to cope with the cotiuously chagig eviromet. Literature is rich with works o idepedet demad ivetory modelig. [4] This provides a theoretical foudatio for the field of ivetory maagemet ad makes it oe of the most developed fields of operatios research. However, it is oted here that the practical implemetatio of ivetory models lags behid the developmet of ivetory modelig. [5] The discrepacy betwee theory ad practice of ivetory is partly caused by the differet goals of academics ad practitioers. [6] Much of the academic research is aimed at rigorous aalysis of uderlyig equatios represetig the ivetory problems ad developig mathematically elegat decisio models. This type of theoretical work is most highly valued by the academic commuity. Therefore, there is ofte less attetio give to providig workable solutios to real problems. Most of the time, the uderlyig mathematical equatios will be made up of umerous mathematical assumptios that make the models practically impossible to provide ay workable solutio for real life problem. Furthermore, learig is the process that acquires kowledge for a system. [7] It is hard to say that the machie is itelliget if it has o learig capability. [8] By defiitio, learig is the activity that eables the ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 786

system to do the same task more efficietly ad more effectively ext time. [9] I particular, learig chages the cotet ad orgaizatio of a system s kowledge eablig it to improve its performace. [10] 2.0 Desig Objectives The desig objectives of this work iclude; 1) Reductio of Mathematical Assumptios: Most of the kow Ivetory Models are mathematical or statistical models ad as such they are ot voided of assumptios. Most of the time, these mathematical assumptios become so complex for ivetory maagers to comprehed ad this hiders the practical applicatio of ivetory models because a uderstadig of the fudametal structure of complex models is the first step ecessary to provide a workable solutio of the problem beig cosidered. Moreover, the mathematical techiques ad other methods are oly aids to maagemet decisio makig. They caot replace the judgmet of huma experts. The developed itelliget system is targeted at reducig these mathematical assumptios to a bearable miimum. 2) Multiple Reorder Levels: Most ivetory models defie a sigle defiite reorder level, but the desiged itelliget model through the use of fuzzy logic defies five reorder levels. This the gives ivetory maagers the opportuity to reorder at ay of the five distict poits ad at ay poit, the quatity that ca be ordered deped o the stock at had. 3) Mobile Ehacemet: Most of the few ivetory models that were implemeted are stad aloe systems (i.e. they are i fixed locatios). This meas that ivetory maagers ca oly moitor their ivetory if ad oly if they are i their offices ad probably load up the ivetory package ad check stock level from time to time. This great barrier is dealt with i the ew system through the mobile ehacemet module (MEM) which delivers real time alerts via SMS to ivetory maagers ad admiistrators eve whe they are very far from their offices. 3.0 Materials Ad Methods Dyamic System Developmet Methodology (DSDM) ad Object-Orieted Aalysis ad Desig Methodology (OOADM) were used i this work. DSDM assumes that all previous steps may be revisited as part of its iterative approach. Therefore, the curret step eed be completed oly eough to move to the ext step, sice it ca be fiished i a later iteratio. This premise is that the busiess requiremets may probably chage ayway as uderstadig icreases, such that ay further work would probably be a waste. Accordig to this approach, the time is take as a costrait i.e. the time is fixed; resources are fixed while the requiremets are allowed to chage. This does ot follow the fudametal assumptio of makig a perfect system the first time, but provides a usable ad useful 80% of the desired system i 20% of the total developmet time. This approach has proved to be very useful uder time costraits ad varyig requiremets. However, the OOADM methodology is used to idetify the objects eeded i the system ad their iterrelatioships. Adequate ad relevat UML diagrams such as class diagram, use case diagram, activity diagram ad etities relatioship (E- R) diagram are geerated which made the codig process quite easy ad straight forward. Most qualities of object orieted programmig such as polymorphism, iheritace, ecapsulatio ad code reusability were all employed i the developmet of the itelliget package which was able to idetify, autheticate ad assig fuctioalities to differet categories of users based o their logi detail. ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 787

The Java 2 Eterprise Editio (J2EE) techology used i the developmet of the system is a very complex techology that iterfaces with several developmet tools. The techology has iterface that is compatible with virtually all Database Maagemet System (DBMS). But the DBMS employed i this work is MySql, which is used to desig back eds of the system (ie data ad kowledge base). Netbea 6.7.1 Itegrated Developmet Eviromet (IDE) is also employed for the developmet of the iferece egie ad busiess logic. Ad for the desig of the frot eds of the work, Adobe CS3 Dreamweaver is used; all the UML diagrams were geerated with Poseido for UML versio 7.0. 4.0 Workig Priciples/Desig The desig ivolved developig a itelliget system that has the ability to lear ew thigs as it is put to use. The loger the system is beig used, the more itelliget it becomes. The learig process is divided ito three modules; 1. Reorder Poit (ROP) Learig Techique The ew model, ulike the Ecoomic Order Quatity (EOQ) model is a multiple reorder level model; which meas that reorder poit is ot just a sigle predetermied poit as is obtaiable with the EOQ model, but orders/reorders ca be placed at five distict poits determied itelligetly by the system usig the equatio give below; (1) Where; ROP is reorder poit; is average daily demad; is stadard deviatio of daily demad. The average (, ad the stadard deviatio of daily demad are determied by the set equatios give below; dk d = k = 1 (2) ( ) 2 d d k 1 σ d = = (3) Where d k is the daily demad at day k ad is the umber of days the product has bee traded upo. By these equatios, average daily demad ad stadard deviatio of daily demad keep chagig o daily bases ad this i tur keeps affectig the value of ROP from time to time. The system is ot ecessarily iterested i the actual value of ROP because whatever the value of ROP is at a particular poit i time will always be calibrated ito five equidistat poits to correspod to the five liguistic values used i the system. The five liguistic values used for ROP are; very small, small, average, big, ad very big. It is obvious from the equatios ad fuzzy learig techique that the loger this system is put to use, the more accurate, more efficiet ad more effective its decisio makig scheme becomes. ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 788

2. Lead-Time Learig Techique Lead-time is the time betwee; whe a order is placed ad whe the physical good is actually delivered. This has bee a problem for EOQ model as the model always assumes a fixed lead-time which is ofte ot accurate. The ew model also addressed the issue of ucertaity associated with lead-time by usig fuzzy learig logic. Istead of fixig or assumig a particular value for lead-time, the ew system defied five district lead-time values withi the ope itervals show below; (4) Where; L max is the maximum lead-time observed i the previous repleishmet; t is time uit (umber of days); is a real umber. Just like ROP, the actual value of lead-time at a particular poit i time is always calibrated ito five equidistat values correspodig to the five fuzzy liguistic values associated to lead-time i this work. These liguistic values are; very short, short, average, log ad very log. 3. Quatity Order Learig Techique Quatity order is the umber of product ordered for at a particular poit i time. Some ivetory models defied a fixed value of product to order wheever the predefied reorder poit is reached. But with this ew model, the size of order to iitiate at a particular poit i time is always determied by the system usig the formula give below; (5) (6) Where Qapp t is the size of order iitiated at day t, S max is maximum stack level, ad S t is the o had ivetory at day t. Rule base of the system The system developed is a sigle atecedet ivetory fuzzy model with five rules; fuzzy iput is the repleishmet lead-time while fuzzy output is the reorder poit (ROP). The rules used are i the form of: IF THEN to relate the iput space ad the output space. R 1 :IF(Lead_Timeis"very short")then (ROPis"very small"); R 2 :IF(Lead_Timeis"short")THEN (ROPis"small"); R 3 :IF(Lead_Timeis"average")THEN (ROPis"average"); R 4 :IF(Lead_Timeis"log")THEN (ROPis"big"); R 5 :IF(Lead_Timeis"very log")then (ROPis"verybig"); ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 789

5.0 Implemetatio The miimum software requiremet of the cliet system is ay graphical user iterface (GUI) operatig system ad ay web browser. The system is compatible with virtually all operatig systems that support etwork ad ay good web browser. However, for the server system, i additio to GUI operatig system ad good browser, the followig software are required; JBOSS Applicatio Server MySql Database Maagemet System Java Developmet Kit (JDK) The miimum hardware requiremets for the cliet systems to ru effectively are as follow; 750MHZ processor speed 128MB RAM size 20GB Hard Disk Drive Network Adapter Scaer or Digital camera for capturig images The miimum hardware requiremets for the server to ru effectively are as follows; 1.77GHZ processor speed 512MB RAM size 80GB Hard Disk Drive Network Adapter Scaer or Digital camera for capturig images 6.0 Results The system developed has the followig features; i. Ca act as a itelliget ivetory model with five reorder poits ii. Is a database that fully employ the cocept of table ormalizatio to keep track of sales ad reorder records iii. It is a model that has bee traslated ito a rule based package which employed the flexibility of fuzzy learig logic ad the architectural desig of J2EE iv. It is a eriched package with the capability of sedig SMS alerts to stock cotrollers ad admiistrators. 7.0 Discussios Most popular ivetory model such as EOQ ad the like always defie a fixed reorder poit value which may work very well mathematically but always fail i real practice. The discrepacy betwee theory ad practice of ivetory is partly caused by the differet goals of academics ad practitioers. [6] This discrepacy ca be reduced to the barest miimum as the ew system is a itelliget package that ca illustrate the workig priciple of the model. This the allows practitioers to make very little iput ad get their desired output. ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 790

Furthermore, the system developed is a merger of two differet products combiig the fuctioalities of ormal ivetory system ad poit of sales (POS) system. It ca be cosidered as a itelliget POS that peeps ito the ivetory to kow what to be sold ad at what rate from time to time. This is achieved through the use of a commo database which acts as sales ad ivetory tracker ad at the same time a reservoir from which ifereces ca be draw for makig critical reorder/sales decisios Agai, the ew system is also eriched with the capability of sedig alerts via SMS to stock cotrollers ad admiistrators eve whe they are far away from their offices. This capability makes it possible for the admiistrator to have iformatio about what happes at various braches of his busiess outfits without visitig the braches. Fially, the system gives real-time iformatio cocerig stock level without maually coutig the items o stock, ulike the other ivetory models that allow some critical trasactios to be doe off lie, oly to be recociled o a later day. As a olie lie system, it is possible to have accurate ad reliable iformatio at all times for more effective stock maagemet. 8.0 Coclusio The sigificace of this system caot be overemphasized. It has bee tested ad foud to be reliable. This system ca be used by ay small scale ad medium eterprises aroud the globe. Its multi-brachig feature makes it suitable for eve big orgaizatios ad maufacturig idustries. The cliet server relatioship of the system (a iheret property of J2EE) eve makes it possible to be hosted o the iteret thereby makig it useful aroud the globe. Refereces [1] Marti K. Star ad David W. Miller (1986); Ivetory Cotrol Theory ad Practice. Pretice- Hall New Jersey, Idia. [2] Fracis (1998:526); Busiess Mathematics ad Statistics. Pretice- Hall New York, USA. Pp. 526 [3] Horgre T. Charles ad Forster George (1987); Cost Accoutig: a Maagerial Emphasis 6 th Editio, Pretice- Hall New York, USA. [4] Flemig, I. (1992); Stock cotrol, OR Isight, Vol. 5 No 4, pp. 9-11 [5] Silver, E.A. (1981); Operatios research i ivetory maagemet, peratios Research, Vol. 29 No. 4, pp. 628-45. [6] Zaakis, S.H., Austie, M. L, Nowadig D. C. ad Silver E. A. (1980) From teachig to implemet ivetory maagemet: problems of traslatio, Iterfaces, Vol. 10, pp. 103-110. [7] Rich, E. ad K. Kight (1991); Artificial Itelligece, 2d Editio, the Uited States of America: McGraw-Hill, Ic. [8] Gisberg, M.L. (1993); Essetials of Artificial Itelligece, the Uited States of America: Morga Kaufma Publishers, Ic. [9] Simo, H.A. (1981); The Scieces of the Artificial, 2d Editio, [10] Cambridge, MA: MIT Press [11] Simo, H.A. (1983); Why should machies lear? Machie [12] Learig: A Artificial Itelligece Approach, CA: Tioga Press. ISSN : 0976-5166 Vol. 2 No. 5 Oct-Nov 2011 791