ISSUES IN LOCATION OF FACILITIES Prof Arun Kanda Department of Mechanical Engg, Indian Institute of Technology, Delhi

Location decisions are STRATEGIC –LIABLE TO AFFECT THE ENTIRE ORGANIZATION –OPERATIVE OVER LONG TIME SPANS –DIFFICULT TO REVERSE –CAPITAL INTENSIVE

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’)

The term ‘FACILITY LOCATION’ emphasizes the generalized approach that handles the variety of above mentioned problems.

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

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

ANNUAL OPERATION EXPENSES CONSIST OF  MATERIALS  TRANSPORTATION  REAL ESTATE TAXES  FUEL COSTS  SUNDRY STATE TAXES  ELECTRIC POWER  WATER

FIXED & VARIABLE COST Annual Cost Volume of Production Location B Location A

MECHANICAL ANALOGUE FOR FINDING BEST LOCATION OF A MANUFACTURING PLANT (ALSO KNOWN AS VARIGNON’S FRAME AFTER INVENTOR)

R2R2 R1R1 RmRm M1M1 M2M2 MnMn 11 22 mm  m+1  m+2  m+n P

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)

MULTI-OBJECTIVE CONSIDERATIONS IN LOCATION DECISIONS FACTORS AFFECTING LOCATION ARE : SUBJECTIVE /OBJECTIVE (labour attitudes) (eg. Costs) INTANGIBLE /TANGIBLE INCOMMENSURATE UNITS

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)

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

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 could be set up X,Y or Z.

Problem Data

OPTIMUM PRODUCTION - DISTRIBUTION SOLUTIONS Product Cost = 192,500 Distn. Cost= 026,450 Total= 218,950

OPTIMUM PRODUCTION - DISTRIBUTION SOLUTIONS (Cont.) Product Cost = 193,750 Distn. Cost= 026,960 Total= 220,710

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

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)

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

Warehouse demands (A-9000), (B-13000), (C-11,000), (D-15,000), (E-8,000) DATA

EVALUATING SHUT DOWN OPTIONS 1

EVALUATING SHUT DOWN OPTIONS (CONT.) 2

EVALUATING SHUT DOWN OPTIONS (CONT.) 3

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1234 * Min Cost for Alternative 3 Hence Shut Down Plant 2 *

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