Modelling study of a container distribution system for high rise factories

CHAPTER INTRODUCTION Singapore is currently the world’s largest transshipment hub and is connected to 600 ports in 123 countries In the year 2002, the Port of Singapore Authority (PSA), handled 17 million TEUs (Twenty-foot Equivalent Units) [1] More than 80% of this volume is transshipment cargo destined for countries other than Singapore This has resulted in 8% annualized growth in container traffic over the past two decades and rapid economic growth in many developing countries To handle the ever increasing container traffic, an entire logistics system is developed comprising of the warehouses and freight stations, road and rail transport, ground handling equipment like straddle carriers and gantry cranes in the port terminals, and larger container ships (in excess of 10,000 TEUs) to benefit from the economies of scale To meet the increased container capacity as well as logistics warehouse space, it is inevitable that warehouses and freight stations will increase in size and more efficient designs and container handling systems are being proposed to increase the throughput and efficiencies Single-storey factories and warehouses are the norm in many countries The container trucks arrive at the docks of the warehouses, where forklifts are driven into the containers for the cargo loading and unloading activities Often, the trailer and the container will be left behind as the loading of the cargo may take up to a day This is inefficient, as this also requires a large tract of land for building the docks and wide roads for the container trucks to be driven to the doorsteps of the warehouses Continuously rising land prices and limited availability of building space are some of the reasons to build factories and warehouses skywards Multi-storey industrial buildings increase the usage of land resources, and this is particularly more significant for countries such as Hong Kong and Singapore, where land is scarce The future trend of factories will be in the form of high-rise buildings Material handling and transportation economies also favor this new trend Vertical movement in multi-storey buildings eliminates longer, slower and costlier horizontal handling of containers in sprawling single-storey factories Compact multi-level design also offers advantage in factory design construction and operation Excavation, foundation, building and maintenance costs are often less per square metre of usable floor space in high-rise buildings compared to single-storey factories The Jurong Town Corporation (JTC) was established in 1968 to plan, develop and manage industrial estates in Singapore Over the last 30 years, JTC has been conscious of the importance of optimizing the use of its industrial land It has done so through intensification of land use, making more productive use of land, and improving the planning and development of the supporting infrastructure It has also been constantly reviewing the allocation policies for industrial and ready-built factories, and revising the planning development of industrial estates and factories Singapore has reached a point in economic growth where it can no longer rely solely on increases in labour and capital investments to fuel further growth It has to focus on productivity gains and innovation for greater output per unit of input [2] Industries that operate in a multi-storey environment are better able to achieve higher land productivity levels than those that not Hence, JTC has been building its factories to higher plot ratios (from 1.8 to 2.5) to increase the efficiency of land use and to encourage industrialists to go high-rise whenever possible These high-rise flatted factories, such as the nine-storey flatted factories located at Woodlands East, are designed to integrate marketing, management, production, storage and other industrial activities They are served by cargo/passenger lifts and loading bays, and some latest factories are designed with ramps that go all the way to the higher floors of these buildings to enable container trucks to transport the cargo to the sheltered loading bays at the entrance of the factory units on every level Hong Kong also solves land scarcity by building industrial facilities that go as high as twenty storeys and ramps that allow vehicular access up to thirteen storeys Although going skywards is the solution to solving land scarcity, building such a large vehicular ramp requires an extensive land area and large capital cost A better alternative system is one that delivers the containers to the various floors of a high-rise factory by other means, instead of the existing vehicular ramp The envisioned factories of the future would be high-rise buildings that incorporate both the office and manufacturing plant in a “single building” Containers will be lifted to the various floors and placed in the container lobby of the factory unit The company would then unload or load the cargo into the container This is more efficient and economical since less land and building cost is incurred to construct the docking areas and the vehicular ramp Furthermore, the empty container can be transported one day prior to loading of the goods and no trailer will be left idling Having the container in the container lobby also provides the extra security compared to leaving the container in the open docks in existing factories The main concern is on the delivery of containers to the various floors of the high-rise factories The final proposed distribution system must allow for the smooth and problem-free movement of containers and reduce operating and maintenance costs Less land and lower capital outlay will be the foremost criteria in proposing a new container distribution system This thesis is organized as follows Chapter first reviews the existing methods of delivering containers to various floors and later proposes a new container distribution system Analytical and simulation studies of the proposed system are presented in Chapters and respectively Chapter discusses the simulation results and a cost analysis is performed to select the optimal crane configuration for uncertain truck arrivals Conclusions are drawn in Chapter 6, together with some recommendations for further study CHAPTER CONTAINER DISTRIBUTION SYSTEMS 2.1 CURRENT CONTAINER DISTRIBUTION SYSTEMS 2.1.1 Vehicular Ramp Incorporated in 1981, ATL Logistics Centre Hong Kong Ltd (a subsidiary of CSX World Terminals) owns and operates ATL Logistics Centre - the world's first and largest intelligent multi-storey drive-in cargo logistics centre (Figure 2.1) [3] (a) (b) (c) (d) Figure 2.1: ATL Logistics Centre in Hong Kong (From [3]) (a) The Main Complex (b) Vehicular Ramp (c) Cargo Being Loaded/Unloaded at Docks (d) Wide Access Roads Inside Buildings Conveniently located in the heart of Kwai Chung Container Terminals and within easy reach of Hong Kong's commercial and population centres, airport and the Mainland border, ATL Logistics Centre offers warehouse and office leasing with a full range of cargo handling, container freight station and distribution services ATL Logistics Centre is made up of two multi-storey warehouses: Centre A and Centre B, comprising of seven and thirteen storeys respectively It consists of a three-lane (two lanes up and one lane down) vehicular ramp to provide direct drive-in access to all levels of the buildings The ramp and internal loading bays are accessible for all vehicular types including 40-ft container trucks The Centre comprises a total floor space of 9.4 million square feet, provides over 1,730 loading bays and handles an average of 8,000 vehicles daily Similar logistics warehouses are also found in Singapore As part of Industrial Land Plan 21 (IP21) [4], JTC has also learnt from Hong Kong by building multi-storey warehouses to solve land scarcity Jurong Port (a subsidiary of JTC) not only is a key bulk and conventional cargo gateway in Singapore, with 23 berths serving over 7,000 vessels every year, it also owns the Jurong Logistics Hub, which is Singapore’s largest multi-storey drive-up warehouse (Figure 2.2) [5] The Hub is a multi-storey drive-up warehouse, which allows 40-ft containers to be trucked to every level, right to the doorsteps of customers and under all weather conditions Strategically located from the Port, Jurong Island, Jurong Industrial Estate and Tuas industrial zone, the ultra-modern warehouse comprises of 118,000 square metres of warehouse space and 6,200 square metres of office space Jurong Logistics Hub's customers include multi-national corporations and logistics providers such as Sony, Volvo, Translink, L’Oreal and Dell Computers (a) (b) (c) (d) Figure 2.2: Jurong Logistics Hub (a) The Main Complex (b) Vehicular Ramp (c) Large Turning Radius (d) Container Left at Dock JTC has also adopted a similar drive-in concept for its stack-up factories to optimize land usage Named Woodlands Spectrum (Figure 2.3) and located in Woodlands East Industrial Park, these high-rise facilities offer ground-floor convenience (through a large ramp for container trucks), private loading areas and car parks The ramp has to be wide enough to accommodate the turning radius of 40-ft trucks and large access roads have to be constructed for easy manoeuvere to reach the units at different levels [6] (a) (b) (c) (d) Figure 2.3: Woodlands Spectrum (a) Overview of One Unit (b) Interior of Vehicular Ramp (c) Wide Access Roads (d) Unloading/Loading Dock Large capital cost is required to construct such a container delivery system and also a large plot of land is required for the building of the vehicular ramps and wide roads Figures from JTC show that the ramp amounts for one-third ($600 million) of the total construction cost (for Woodlands Spectrum) It is ironical that what causes factories to move skywards (to optimize land space and cost) in the beginning ends up with a design using a large plot of land for the vehicular ramps and wide roads, and incurs a large capital cost A solution to this would be a new system of delivering the containers to the various floors of the multi-storey factories without using a large vehicular ramp 2.1.2 Container Hoisting Crane One of the key objectives of this research is to propose a new and innovative method of delivering the containers to each and every unit’s doorsteps without utilizing the direct drive-in model of the vehicular ramp Since the item being transported is the 20-ft and 40-ft ISO containers, the handling methods at maritime terminals may provide suitable alternatives Using cranes to transport the containers is a tried-andtested efficient distribution method and the crane design can be incorporated in the vertical hoisting of the containers to various floors of the buildings The small ground area required, the low dead weight and the resulting low load on the building are some of the advantages that illustrate the expediency and economy of using container cranes In fact, container cranes had already been implemented in many high-rise factories and warehouses around the world A customer list (Table 2.1) obtained from Mannesmann Demag (a company that manufactures and installs container hoists) shows that Hong Kong has many high-rise factories and warehouses that utilize container cranes to deliver the containers to the various floors Table 2.1: Customer List from Mannesmann Demag Reference List (Container Hoist Installations) No of storeys Year of Customer Country served Construction (plus ground floor) Kowloon Wharf Hong Kong 11 1972 Kowloon Wharf Hong Kong 11 1972 Kowloon Wharf Hong Kong 15 1975 Kowloon Wharf Hong Kong 14 1975 Taikoo Hong Kong 1977 Tai Sang Land Hong Kong 1980 Development Singapore Singapore 12 1981 Warehouse Singapore Singapore 12 1981 Warehouse Swire Bottlers Hong Kong 1981 Tai Sang Land Hong Kong 17 1981 Development Tina’ Enterprise Hong Kong 14 1982 Southwinds Land Hong Kong 15 1982 & Investments The machine room with the hoist and electrical equipment, the hoist shaft outside or inside the building with horizontal travel tracks into the lobbies, the vertical guidance system, the spreader and the various container positions in the lobby, all form a single unified system Each floor has a control panel from which the operator starts and monitors all functions for the particular lobby Display panels provide information on the operations currently being carried out and on those that have been completed The container truck delivering the container will first position itself underneath the hoisting crane The crane, guided by vertical beams, will be lowered and the selfadjusting spreader will then lift up the container to the pre-selected level Selection of the optimum lifting speed is dependent on the number of floors and the number of containers to be handled per hour Once it has been lifted to the level, the spreader will 10 new replication In this way, the matchup of the random numbers across alternatives will remain synchronized beyond the first replication This section covers some of the techniques that have been developed for analyzing simulation output processes, particularly for terminating simulations Further treatment of the methods discussed in this section are presented in books that deal with discrete-event simulation [50,54], references on simulation output analysis [55,56] and tutorials of the Winter Simulation Conference [57-60] 66 CHAPTER RESULTS AND DISCUSSION The results of the terminating simulations for various crane configurations (Figure 2.13) and traffic conditions (average truck arrival rates) are presented in this chapter The five performance measures presented in Chapter are used as a means of comparison between the crane configurations The average truck arrival rates are evaluated from the average number of trucks that enter the proposed factory within each day (i.e from 8am to 5pm) For instance, a minimum truck arrival rate of 0.1667 Trucks/min (90 Trucks per day) is chosen as each of the ninety units in the factory is assumed to handle at least one container each day In this study, it is assumed that no crane breaks down during the daily operations as the cranes are assumed to be perfectly reliable with regular servicing and maintenance Different range of average truck arrival rates are used for the different crane configurations For instance, the two-crane configuration is studied for average truck arrival rates from 0.1667 to 0.2963 Trucks/min, whereas the three-crane configuration is studied from 0.1667 to 0.4537 Trucks/min The average crane service time per truck is estimated to be 6.5 minutes If two cranes are employed for the proposed factory, the cranes can only handle up to a maximum of 166 trucks each day Hence the maximum truck arrival rate is 0.2963 Trucks/min (160 Trucks per day) Similarly, when three cranes are used, the maximum truck arrival rate is 0.4537 Trucks/min (245 Trucks per day) The numerical results are presented in Table 5.1 The table shows the expected average values and 200 simulation replications are chosen so that the ratio of the confidence interval half width to the interval falls within a small tolerance of 0.10 67 Table 5.1: Performance Measures for the Various Crane Configurations Two-crane Configuration Truck Arrival Rate Trucks/day Trucks/min 90 0.1667 110 0.2037 135 0.2500 150 0.2778 160 0.2963 Wq Ws Lq Ls (mins) 3.1523 5.0929 9.5510 14.7971 19.8386 (mins) 9.6457 11.5900 16.0474 21.2951 26.3370 (Trucks) 0.5461 1.0797 2.4801 4.2768 6.1108 (Trucks) 1.6318 2.3936 4.0725 6.0133 7.9264 ρ 0.5428 0.6570 0.7962 0.8682 0.9078 Three-crane Configuration Type I Truck Arrival Rate Trucks/day Trucks/min 90 0.1667 110 0.2037 135 0.2500 150 0.2778 160 0.2963 180 0.3333 200 0.3704 225 0.4167 245 0.4537 Wq Ws (mins) 1.7766 2.4992 3.6941 4.6747 5.4371 7.6067 10.8385 17.3235 24.9271 (mins) 8.2693 8.9960 10.1919 11.1728 11.9355 14.1051 17.3369 23.8226 31.4262 Lq Ls (Trucks) 0.3053 0.5237 0.9507 1.3306 1.6590 2.6181 4.1588 7.5041 11.8078 (Trucks) 1.3852 1.8433 2.5638 3.1123 3.5555 4.7420 6.4975 10.0813 14.5327 ρ 0.3600 0.4399 0.5377 0.5939 0.6321 0.7080 0.7796 0.8591 0.9083 Three-crane Configuration Type II Truck Arrival Rate Trucks/day Trucks/min 90 0.1667 110 0.2037 135 0.2500 150 0.2778 160 0.2963 180 0.3333 200 0.3704 225 0.4167 245 0.4537 Wq Ws Lq Ls (mins) 1.5233 2.1465 3.2026 4.0923 4.7317 6.8028 9.7589 16.0076 23.8068 (mins) 8.0166 8.6432 9.7014 10.5914 11.2300 13.3012 16.2573 22.5060 30.3058 (Trucks) 0.2618 0.4485 0.8207 1.1715 1.4314 2.3403 3.7539 6.9009 11.1989 (Trucks) 1.3387 1.7678 2.4355 2.9596 3.3317 4.4828 6.1091 9.4865 13.9322 ρ 0.3590 0.4398 0.5383 0.5960 0.6335 0.7142 0.7850 0.8619 0.9111 68 Four-crane Configuration Type I Truck Arrival Rate Trucks/day Trucks/min 90 0.1667 110 0.2037 135 0.2500 150 0.2778 160 0.2963 180 0.3333 200 0.3704 225 0.4167 245 0.4537 270 0.5000 290 0.5370 315 0.5833 330 0.6111 Wq Ws (mins) 1.0999 1.4489 1.9739 2.3240 2.6289 3.3034 4.1733 5.7609 7.5215 10.7592 15.1186 22.0397 26.8406 (mins) 7.5930 7.9458 8.4719 8.8217 9.1271 9.8021 10.6724 12.2597 14.0209 17.2585 21.6162 28.5372 33.3381 Lq Ls (Trucks) 0.1892 0.3029 0.5031 0.6574 0.7956 1.1258 1.5843 2.4669 3.4913 5.5145 8.3614 13.3474 17.1317 (Trucks) 1.2763 1.6245 2.1198 2.4506 2.7070 3.2794 3.9661 5.1488 6.3916 8.6730 11.7103 16.8771 20.7474 ρ 0.2721 0.3306 0.4061 0.4500 0.4790 0.5404 0.5973 0.6730 0.7266 0.7919 0.8393 0.8852 0.9058 Four-crane Configuration Type II Truck Arrival Rate Trucks/day Trucks/min 90 0.1667 110 0.2037 135 0.2500 150 0.2778 160 0.2963 180 0.3333 200 0.3704 225 0.4167 245 0.4537 270 0.5000 290 0.5370 315 0.5833 330 0.6111 Wq Ws Lq Ls (mins) 0.9498 1.2550 1.7061 2.0149 2.2594 2.8384 3.5475 4.7086 6.0115 8.0545 10.7755 16.0227 20.6790 (mins) 7.4440 7.7525 8.2047 8.5133 8.7587 9.3364 10.0459 11.2078 12.5108 14.5533 17.2723 22.5199 27.1767 (Trucks) 0.1631 0.2618 0.4327 0.5664 0.6820 0.9700 1.3361 2.0070 2.7978 4.0977 5.9190 9.5988 12.9957 (Trucks) 1.2453 1.5857 2.0402 2.3521 2.5945 3.1240 3.7261 4.6922 5.7131 7.2775 9.3177 13.2213 16.7334 ρ 0.2709 0.3313 0.4034 0.4483 0.4796 0.5396 0.6005 0.6713 0.7300 0.7954 0.8521 0.9073 0.9353 69 Average Waiting Time Per Truck in in Queue Truck Arrival Rates Rates Average Waiting Time Per Truck Queue(Wq) ( Wqvs ) vs Truck Arrival 30 25 Time (mins) 20 Two-crane Three-crane Type I 15 Three-crane Type II Four-crane Type I Four-crane Type II 10 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Truck Arrival Rate (Trucks/min) Figure 5.1: Curves of the Average Waiting Time Per Truck in Queue ( Wq ) versus Truck Arrival Rates (Trucks/min) Average Time Per Truck Spent in System (Ws) vs Truck Arrival Rates Average Time Per Truck Spent in System ( Ws ) vs Truck Arrival Rates 40 35 Time (mins) 30 Two-crane 25 Three-crane Type I 20 Three-crane Type II Four-crane Type I 15 Four-crane Type II 10 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Truck Arrival Rate (Trucks/min) Figure 5.2: Curves of the Average Time Per Truck Spent in System ( Ws ) versus Truck Arrival Rates (Trucks/min) 70 Average of Trucks Waiting Queue( (Lq) ruck Arrival Rates Average No ofNo Trucks Waiting ininQueue vsTTruck Arrival Rates Lq )vs 18 16 14 Trucks 12 Two-crane Three-crane Type I 10 Three-crane Type II Four-crane Type I Four-crane Type II 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Truck Arrival Rate (Trucks/min) Figure 5.3: Curves of the Average Number of Trucks Waiting in Queue ( Lq ) versus Truck Arrival Rates (Trucks/min) Average No of Trucks in System (Ls) vs Truck Arrival Rates Average No of Trucks in System ( Ls ) vs Truck Arrival Rates 25 20 Two-crane 15 Trucks Three-crane Type I Three-crane Type II Four-crane Type I 10 Four-crane Type II 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Truck Arrival Rate (Trucks/min) Figure 5.4: Curves of the Average Number of Trucks in System ( Ls ) versus Truck Arrival Rates (Trucks/min) 71 Average Crane Utilization Arrival Rates Average Crane Utilizationvs vsTruck Truck Arrival Rates 1.0 0.9 0.8 Crane Utilization 0.7 Two-crane 0.6 Three-crane Type I 0.5 Three-crane Type II Four-crane Type I 0.4 Four-crane Type II 0.3 0.2 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Truck Arrival Rate (Trucks/min) Figure 5.5: Curves of the Average Crane Utilization (ρ) versus Truck Arrival Rates (Trucks/min) Figures 5.1 to 5.5 present the performance measures for various crane configurations and truck arrival rates From Figures 5.1 to 5.4, it may be observed that the average truck waiting time and the number of trucks in both queue and system decrease as more cranes are used The increase in flexibility of the crane (i.e from Type I to Type II), also results in an improvement in the performance of the factory Lower delay is encountered as the cranes are more efficiently utilized (less period of idleness) and as a result, the average crane utilization also increases This improvement is more significant as the truck arrival rates increase Although the study produces a number of performance measures, an overall cost measure is proposed, on which easy comparisons across the configurations can be performed 72 The cost measure is categorized as 1) Capital Cost, 2) Operating Cost, and 3) Opportunity Cost due to trucks waiting for service The cost analysis is presented below: Cost Analysis Types of Cost: 1) 2) Capital Cost Cost of Each Crane = $1 000 000 Annual Depreciation Cost (DC) of Each Crane1 = $ 100 000 Electricity Charges2 = $0.1240/kWh Crane Power Rating3 = 250 kW Annual Operating Cost (OC) of Each Crane = $ 101 835 = $ 200 000 = $35/hr Operating Cost (Based on hrs of operations daily and 100% Utilization) Annual Maintenance Cost (MC) of Each Crane (Based on 20% of equipment cost) 3) Opportunity Cost Waiting Cost per Truck4 Note: A crane is typically written off over 10 years on a straight-line basis Based on utilities rates (w.e.f July 2003) during peak period (7am to 11pm) for Extra High Tension Electricity from SP Services Ltd [61] Based on the power rating of rubber tyred gantry crane from KCI Konecranes [62] Based on local truck hiring service charges 73 The detailed costing for the various crane configurations and truck arrival rates are presented in Table 5.2 Table 5.2: Summary of Costing Two-crane Configuration Truck Arrival Rate Trucks/day Trucks/min Annual DC ($) 90 110 135 150 160 0.1667 0.2037 0.2500 0.2778 0.2963 200 000 200 000 200 000 200 000 200 000 Annual OC ($) Annual MC ($) 55 276 66 906 81 081 88 413 92 446 400 000 400 000 400 000 400 000 400 000 Annual Waiting Cost ($) 60 406 119 280 274 532 472 582 675 835 Annual Total Cost ($ m) 0.77 0.85 1.04 1.25 1.46 Annual Waiting Cost ($) 34 044 58 533 106 182 149 298 185 224 291 527 461 539 829 904 300 312 Annual Total Cost ($ m) 1.04 1.09 1.17 1.23 1.28 1.41 1.60 1.99 2.48 Annual Waiting Cost ($) 29 190 50 273 92 055 130 698 161 193 260 717 415 566 766 864 241 872 Annual Total Cost ($ m) 1.04 1.08 1.16 1.21 1.25 1.38 1.56 1.93 2.42 Three-crane Configuration Type I Truck Arrival Rate Trucks/day Trucks/min Annual DC ($) 90 110 135 150 160 180 200 225 245 0.1667 0.2037 0.2500 0.2778 0.2963 0.3333 0.3704 0.4167 0.4537 300 000 300 000 300 000 300 000 300 000 300 000 300 000 300 000 300 000 Annual OC ($) Annual MC ($) 109 982 134 392 164 270 181 439 193 110 216 298 238 172 262 459 277 490 600 000 600 000 600 000 600 000 600 000 600 000 600 000 600 000 600 000 Three-crane Configuration Type II Truck Arrival Rate Trucks/day Trucks/min Annual DC ($) 90 110 135 150 160 180 200 225 245 0.1667 0.2037 0.2500 0.2778 0.2963 0.3333 0.3704 0.4167 0.4537 300 000 300 000 300 000 300 000 300 000 300 000 300 000 300 000 300 000 Annual OC ($) Annual MC ($) 109 676 134 361 164 453 182 081 193 537 218 192 239 821 263 315 278 346 600 000 600 000 600 000 600 000 600 000 600 000 600 000 600 000 600 000 74 Four-crane Configuration Type I Truck Arrival Rate Trucks/day Trucks/min Annual DC ($) 90 110 135 150 160 180 200 225 245 270 290 315 330 0.1667 0.2037 0.2500 0.2778 0.2963 0.3333 0.3704 0.4167 0.4537 0.5000 0.5370 0.5833 0.6111 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 Annual OC ($) Annual MC ($) 110 837 134 667 165 421 183 303 195 116 220 127 243 304 274 140 295 973 322 573 341 880 360 577 368 969 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 Annual Waiting Cost ($) 21 077 33 934 56 737 74 223 89 558 126 603 177 713 275 983 392 356 618 520 933 511 478 175 885 888 Annual Total Cost ($ m) 1.33 1.37 1.42 1.46 1.48 1.55 1.62 1.75 1.89 2.14 2.48 3.04 3.45 Annual Waiting Cost ($) 18 201 29 393 49 040 64 351 76 970 108 782 151 064 225 571 313 587 463 033 665 342 074 622 452 958 Annual Total Cost ($ m) 1.33 1.36 1.41 1.45 1.47 1.53 1.60 1.70 1.81 1.99 2.21 2.64 3.03 Four-crane Configuration Type II Truck Arrival Rate Trucks/day Trucks/min Annual DC ($) 90 110 135 150 160 180 200 225 245 270 290 315 330 0.1667 0.2037 0.2500 0.2778 0.2963 0.3333 0.3704 0.4167 0.4537 0.5000 0.5370 0.5833 0.6111 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 400 000 Annual OC ($) Annual MC ($) 110 348 134 952 164 321 182 611 195 360 219 801 244 608 273 447 297 358 323 998 347 094 369 580 380 985 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 800 000 75 Annual Total Cost vs Truck Arrival Rates 4.0 Annual Total Cost ($ million) 3.5 3.0 Two-crane 2.5 Three-crane Type I 2.0 Three-crane Type II Four-crane Type I 1.5 Four-crane Type II 1.0 0.5 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 Truck Arrival Rate (Trucks/min) Figure 5.6: Curves of Annual Total Cost versus Truck Arrival Rates (Trucks/min) Figure 5.6 provides a useful visualization to aid in the selection of an optimum crane configuration for various truck arrival rates For instance, when the truck arrival rate is below 0.28 Trucks/min, two cranes are sufficient to service the relatively low number of trucks When the arrival rate exceeds 0.28 Trucks/min, two cranes are inadequate to service the trucks and the cost increases as a result of higher truck waiting times In this case, an additional crane is required Similarly, a fourth crane is required when the truck arrival rate exceeds 0.38 Trucks/min Within the same number of cranes used, a lower cost is achieved by allowing higher flexibility in the crane allocation among the columns It should be noted that the cost analysis is performed on the basis that no crane breaks down during the daily operations Although two cranes are shown to be adequate when the truck arrival rate is below 0.28 Trucks/min, it is recommended that the factory employs three cranes in order to be prepared for the breakdown of one of 76 the cranes If three cranes are used, the factory is still able to operate efficiently even when one of the cranes breaks down It is estimated that each factory unit is handling a maximum of two containers, or a total load of 180 containers (0.33 Trucks/min) each day Hence, an additional 25 containers can be catered by using three cranes The average number of trucks in the queueing area for the suggested range of truck arrival rates is obtained from Figure 5.3 Table 5.3 gives a quick reference for selecting the optimal number of cranes and required size of the queueing area for different truck arrival rates Table 5.3: Crane Selection Reference Truck Arrival Rate (Trucks/min) Optimum No of Cranes Average Crane Utilization Average No of Trucks in Queue Annual Total Cost (million) 0.17 – 0.28 (90 – 150 Trucks) 0.28 – 0.38 (150 – 205 Trucks) > 0.38 (> 205 Trucks) 54% - 87% 60% - 80% > 60% >2 $0.77 – $1.25 $1.21 - $1.57 > $1.60 77 CHAPTER CONCLUSIONS AND RECOMMENDATIONS In this study, a new and innovative system of delivering containers to high-rise factories or warehouses by utilizing overhead cranes is proposed This system requires less building space and capital cost compared to the current drive-in system of the vehicular ramp The first part of the study involves a comparison of the different existing systems of delivering containers to high-rise factories and warehouses and a proposal of a new container distribution system and factory design The second part involves an attempt to study the operation of the proposed factory by using an analytical approach, which only provides bounds for the various performance measures A simulation study is then performed as an alternative to analyze the factory’s operation to determine the optimum number of cranes for various truck arrival rates The analytical study does not provide any closed form solutions, however, it provides bounds for the simulation results, thereby increasing the validity and credibility of the simulation model The simulation results and cost analysis are used in designing the proposed factory The optimum number of cranes to be employed for various traffic conditions (truck arrival rates) is three This configuration may handle up to 205 containers each day, and is capable of handling the requirements of the factory when a crane fails The average waiting time per truck in queue is between four to ten minutes and the average crane utilization lies in the acceptable range of 60% to 80% A queueing area for four trucks is recommended 78 It is important to note that the simulation results are based on the assumption of constant truck arrival rates throughout the operational period and a symmetrical allocation of the incoming trucks to the columns With a nonstationary truck arrival pattern, different simulation results may be produced For instance, the factory could have been simulated with a truck arrival rate that varies throughout the operational period This may help aid in determining if the factory is able to handle the peak traffic conditions at a particular period An unsymmetrical allocation of the incoming trucks to the columns could also be simulated The allocation of the trucks to the columns has an effect on the performance of the crane configurations For instance, when more trucks are designated for the central columns (i.e Columns 4-6) the management may assign two cranes to service the three columns, leaving the other two cranes to handle the rest of the columns on each end (for the four-crane configuration) Another area that needs further study is the crane configurations From the simulation results, increasing the flexibility of the crane allocation for the same number of cranes, not only results in a lower average truck waiting time, but also allows more containers to be handled, as the crane’s utilization increases However, this may incur a higher overhead as more complicated hardware and software is required for the dynamic assignment of the cranes to the columns It is recommended that more crane allocation configurations be analyzed in order to select an optimum configuration Another research issue could focus on the scheduling of the truck arrivals With proper scheduling, more trucks can be serviced with the same amount of resources, thereby increasing the throughput of the factory 79 The model that is developed in this thesis has provided valuable insights of the factory’s operations and can detect potential bottlenecks in the factory design The results of the simulation study may be used in the implementation of the proposed container distribution system for future high-rise factories or warehouses The outcome of this modelling study has laid the groundwork for its transition into a useful analysis tool for such container distribution systems for high-rise factories 80 ... 2.1) obtained from Mannesmann Demag (a company that manufactures and installs container hoists) shows that Hong Kong has many high- rise factories and warehouses that utilize container cranes to... arrival rates is analyzed 24 CHAPTER ANALYTICAL STUDY OF PROPOSED CONTAINER DISTRIBUTION SYSTEM Queueing arises whenever there is more demand for service than there is capacity for service available... land area and large capital cost A better alternative system is one that delivers the containers to the various floors of a high- rise factory by other means, instead of the existing vehicular ramp