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ISSUES IN LOCATION OF FACILITIES Prof Arun Kanda Department of Mechanical Engg, Indian Institute of Technology, Delhi
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Location decisions are STRATEGIC –LIABLE TO AFFECT THE ENTIRE ORGANIZATION –OPERATIVE OVER LONG TIME SPANS –DIFFICULT TO REVERSE –CAPITAL INTENSIVE
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HIERARCHY OF LOCATION PROBLEMS Location of ‘Plant’ Plant Layout ( Location of ‘Depts’) Physical Arrangements of M/cs Work Place Layout ( Location of ‘tools’ or ‘raw materials’)
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The term ‘FACILITY LOCATION’ emphasizes the generalized approach that handles the variety of above mentioned problems.
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LOCATION DECISIONS ARE DYNAMIC Owing to changing technology, competition, change of consumer tastes, decisions like –NEW PLANTS –EXPANSION –DECENTRALIZATION –PLANT SHUTDOWN ARE CONSTANTLY UNDER REVIEW
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IMPORTANT FACTORS IN LOCATION MARKET RAW MATERIALS TRANSPORTATION POWER CLIMATE AND FUEL LABOUR AND WAGES LAWS AND TAXATION COMMUNITY SERVICES WATER AND WASTE GOVT. INCENTIVES
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ANNUAL OPERATION EXPENSES CONSIST OF MATERIALS TRANSPORTATION REAL ESTATE TAXES FUEL COSTS SUNDRY STATE TAXES ELECTRIC POWER WATER
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FIXED & VARIABLE COST Annual Cost Volume of Production Location B Location A
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MECHANICAL ANALOGUE FOR FINDING BEST LOCATION OF A MANUFACTURING PLANT (ALSO KNOWN AS VARIGNON’S FRAME AFTER INVENTOR)
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R2R2 R1R1 RmRm M1M1 M2M2 MnMn 11 22 mm m+1 m+2 m+n P
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In the absence of friction, the common knot P of (m+n) strings comes to equilibrium at least Cost location [Here we draw an analogy between Min. Potential Energy & Min. Travel Cost ] Assumptions: R 1, R 2, ……R m Locations of Raw Material Sources M 1,M 2 …Mn location of markets Euclidean (Straight tine travel) Each weight (there are m+n in all Wi= No. of annual trips between P and that pt X (Cost per unit distance)
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MULTI-OBJECTIVE CONSIDERATIONS IN LOCATION DECISIONS FACTORS AFFECTING LOCATION ARE : SUBJECTIVE /OBJECTIVE (labour attitudes) (eg. Costs) INTANGIBLE /TANGIBLE INCOMMENSURATE UNITS
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A Decision Matrix approach with proper evaluation of weights of factors, Normalization of scores can help in ranking alternative locations. (THIS IS DEMONSTRATED THROUGH A CASE STUDY)
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A P1P1 P2P2 B C Y X Z E D P 1 Existing plant P 2 Existing plant A,B,C,D,EWarehouses X,Y,ZPossible Locations for new plant
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Owing to increase of weekly demand to 72,000 there is a capacity deficit of 25,000/wk and it is felt that a plant of capacity 25000 could be set up X,Y or Z.
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Problem Data
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OPTIMUM PRODUCTION - DISTRIBUTION SOLUTIONS Product Cost = 192,500 Distn. Cost= 026,450 Total= 218,950
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OPTIMUM PRODUCTION - DISTRIBUTION SOLUTIONS (Cont.) Product Cost = 193,750 Distn. Cost= 026,960 Total= 220,710
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OPTIMUM PRODUCTION -DISTRIBUTION SOLUTIONS (Cont.) Product Cost = 192,000 Distn. Cost= 026,400 Total= 218,400* (* MINIMUM) (Demand and Capacity in thousands) hence choose plant at size Z
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LOCATIONAL DYNAMICS Suppose third plant is set up at site Z. After some time demand drops from, 72,000 to 56,000 per week Which plant to shut down ? Which to run at partial capacity ? (These are again location decisions)
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ALTERNATIVES for investigation : 1.Run all plants at partial capacity 2.SHUT DOWN P1, Use Overtime in others 3. SHUT DOWN P2, Use Overtime in others 4. SHUT DOWN Z, Use Overtime in others
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Warehouse demands (A-9000), (B-13000), (C-11,000), (D-15,000), (E-8,000) DATA
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EVALUATING SHUT DOWN OPTIONS 1
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EVALUATING SHUT DOWN OPTIONS (CONT.) 2
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EVALUATING SHUT DOWN OPTIONS (CONT.) 3
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1234 * Min Cost for Alternative 3 Hence Shut Down Plant 2 *
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Summary The strategic importance of location decisions Hierarchy of Location decisions Analogue model for Facility location Important factors in plant location A case study on new plant location and shut down under dynamic conditions. Multi-objective plant location case to be studied in the next lecture along with facility location models
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