Studying and building automated storage and retrieval algorithm in cold warehouse

VIET NAM NATIONAL UNIVERSITY HO CHI MINH CITY HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY TRUONG NGOC CUONG STUDYING AND BUILDING AUTOMATED STORAGE AND RETRIEVAL ALGORITHM IN COLD WAREHOUSE NGHIÊN CỨU XÂY DỰNG GIẢI THUẬT LƯU TRỮ VÀ TRUY HỒI HÀNG HÓA TỰ ĐỘNG TRONG KHO LẠNH Major: Mechatronic Engineering ID Code: 60520114 MASTER THESIS HO CHI MINH CITY, December 2018 i CƠNG TRÌNH ĐƯỢC HỒN THÀNH TẠI TRƯỜNG ĐẠI HỌC BÁCH KHOA –ĐHQG -HCM Cán hướng dẫn khoa học 1: TS Phùng Trí Cơng Cán hướng dẫn khoa học 2: PGS Nguyễn Duy Anh Cán chấm nhận xét 1:TS Nguyễn Huy Hùng Cán chấm nhận xét 2:PGS.TS Nguyễn Thanh Phương Luận văn thạc sĩ bảo vệ Trường Đại học Bách Khoa, ĐHQG Tp HCM ngày 20 tháng 12 năm 2018 Thành phần Hội đồng đánh giá luận văn thạc sĩ gồm: (Ghi rõ họ, tên, học hàm, học vị Hội đồng chấm bảo vệ luận văn thạc sĩ) PGS.TS Nguyễn Quốc Chí TS Đồn Thế Thảo TS Nguyễn Huy Hùng PGS.TS Nguyễn Thanh Phương TS Lê Thanh Hải Xác nhận Chủ tịch Hội đồng đánh giá LV Trưởng Khoa quản lý chuyên ngành sau luận văn sửa chữa (nếu có) CHỦ TỊCH HỘI ĐỒNG TRƯỞNG KHOA………… i ĐẠI HỌC QUỐC GIA TP.HCM CỘNG HÒA XÃ HỘI CHỦ NGHĨA TRƯỜNG ĐẠI HỌC BÁCH KHOA VIỆT NAM Độc lập - Tự - Hạnh phúc NHIỆM VỤ LUẬN VĂN THẠC SĨ Họ tên học viên: Trương Ngọc Cường MSHV: 1770205 Ngày, tháng, năm sinh: 01/02/1994 Nơi sinh: Bà Rịa Vũng Tàu Chuyên ngành: Kỹ Thuật Cơ Điện Tử Mã số: 60520114 I TÊN ĐỀ TÀI: Nghiên cứu xây dựng giải thuật lưu trữ truy hồi hàng hóa tự động kho lạnh II NHIỆM VỤ VÀ NỘI DUNG: Khảo sát thực trạng kho lạnh Việt Nam, Nghiên cứu giải thuật lưu trữ hàng hóa kho dựa phương thức tối ưu hóa vị trí hoạch định đường ngắn Xây dựng mơ hình kho với 480 chứa pallet phần mềm quản lý kho tối ưu III NGÀY GIAO NHIỆM VỤ : 15/01/2018 IV NGÀY HOÀN THÀNH NHIỆM VỤ: 02/12/2018 V CÁN BỘ HƯỚNG DẪN : TS Phùng Trí Cơng - PGS.TS Nguyễn Duy Anh CÁN BỘ HƯỚNG DẪN Tp HCM, ngày tháng năm 20 (Họ tên chữ ký) CHỦ NHIỆM BỘ MÔN ĐÀO TẠO (Họ tên chữ ký) TS Phùng Trí Cơng CÁN BỘ HƯỚNG DẪN (Họ tên chữ ký) PGS TS Nguyễn Duy Anh TRƯỞNG KHOA KHOA CƠ KHÍ (Họ tên chữ ký) ii ACKNOWLEDGEMENT I would like to send my deepest gratitude to Dr Phung Tri Cong and Assoc Prof Nguyen Duy Anh for his devotion and guidance which are a great motivation for me to overcome difficulties of the thesis I would especially like to acknowledge the support of teachers at Faculty of Mechanical Engineering, Ho Chi Minh City University of Technology who has guided me over the past six years, the knowledge teachers have taught is really precious and is the foundation for me to complete the project My family and friend continues to amaze me with their constant love and support Without your help during my studies and through my life I would not be all that what I am right now Thank you! Truong Ngoc Cuong i ABSTRACT An effectiveness of a storage and retrieval system in cold warehouse is assessed based on operating costs, which can be improved by re-designing warehouse layout or upgraded to automated system But cost intensive and high time consumption are gating to implement those proposals In this thesis, an improvement is considered through minimize the expected travel distance of two optimal criteria are determining storage location algorithm and path planning in narrow aisle racking system A warehouse layout is designed for 480 storage locations on 16 pallet racking, separated by storage aisles and pick aisle Storage and retrieval of goods is carried out by forklift trucks The system is able to deal with variations in environment conditions such as deadlocks or traffic jams by applying the windows time concept combine with A-star algorithm Simulated results show that proposal algorithm help to reduce up to 29% travel distance compared with traditional policies Tính hiệu hệ thống lưu trữ truy hồi hàng hóa kho lạnh đánh giá dựa chi phí vận hành cải thiện cách bố trí lại khơng gian kho nâng cấp lên hệ thống tự động Nhưng chi phí cao tốn thời gian dài trở ngại để thực đề xuất Trong luận văn này, việc giảm chi phí kho thực cách rút ngắn quãng đường di chuyển hàng hóa dựa hai yếu tố tối ưu hóa giải thuật tìm kiếm vị trí lưu trữ kệ chứa hoạch định đường ngắn cho nhiệm vụ xe nâng kho lạnh có lối hẹp (single aisle) Mơ hình kho lạnh thiết kế với dung tích 480 chứa bố trí 16 kệ Các dãy kệ ngăn cách lối lối phụ Việc lưu trữ truy hồi hàng hóa thực xe forklift Hệ thống có khả xử lý số biến thể môi trường ách tắc giao thông bị tê liệt giải thuật giám sát theo thời gian kết hợp với giải thuật tìm đường thuật tốn A-star Kết mô cho thấy giải thuật đề xuất giúp giảm đến 29% tổng quãng đường di chuyển hàng hóa so với giải thuật lưu trữ truyền thống ii DECLARATION I pledge that the thesis Studying and building automated storage and retrieval algorithm in cold warehouse is my own research It is entirely of my own work and has not been submitted to any other college or higher institution, or for any other academic award in this College The data and materials in the dissertation are truthful and all references, inheritance are cited and fully referenced Truong Ngoc Cuong iii TABLE OF CONTENTS ACKNOWLEDGEMENT .i ABSTRACT ii DECLARATION iii TABLE OF CONTENTS v LIST OF FIGURES LIST OF ACRONYMS Motivation Literature Review 1.2.1 Warehousing operations 1.2.2 Most common mode of pallet racking systems in Vietnam .4 1.2.3 Storage Policy 1.2.4 Planning path 12 Research problem 14 Objectives 15 Thesis structure 15 Chapter 2: METHODOLOGY .12 2.1 Assumption and Layout design 12 2.1.1 Assumption [1-2] .12 2.1.2 Warehouse layout and Routing 12 2.2 Forklift Truck – System configuration and kinematic modeling 13 2.3 Auto – Localization Algorithm 16 2.3.1 Basic of ABC, COL policy and continuous cluster method 16 2.3.2 Storage and retrieval strategy base on A-star Algorithm 22 2.4 Dynamic Routing by time windows method 23 Chapter 3: SIMULATED SOFTWARE DEVELOPMENT 28 v 3.1 Data structure 28 3.2 Main program 29 3.3 Software Interfacing 35 Chapter 4: SIMULATED RESULT AND DISCUSSION 37 4.1 Travel distance improvement under localization policy 37 4.2 The efficiency of dynamic routing algorithm by travel distance comparison ……………………………………………………………………… 40 Chapter 5: CONCLUSION & FUTURE WORK 42 Chapter 6: REFERENCES 44 vi List of Figures LIST OF FIGURES Figure 1.1: Overall Warehouse management activity………………………………… Figure 1.2: Warehouse Operating …………………………………………………… Figure 1.3 Selective Pallet Racking in cold warehouse………………………… ….4 Figure 1.4 Adjustable pallet racking for narrow aisles……………………… ………5 Figure 1.5 Mobile pallet racking system …………………………………………… Figure 1.6 Storage policy……………………………………………………….…….7 Figure 1.7 A typical Zone positioning for three class in a square in rack…….………9 Figure 1.8 Static routing problem…………………………………………… …….14 Figure 2.1: Warehouse layout ……………………………………………………… 13 Figure 2.2: An industrial forklift truck ……………………………………………….14 Figure 2.3: Kinematics model of a forklift ………………………………………… 14 Figure 2.4: ABC storage policy ………………………………………………………16 Figure 2.5: Continuous cluster concept …………………………………………… 17 Figure 2.6: Storage location under Continuous cluster policy …………………….…18 Figure 2.7: The mapping model in simulation ……………………………………….21 Figure 2.8: Travel Distance Index for Rack S-III ……………………………………22 Figure 2.9: Deadlock and Traffic Jams ………………………………………………27 Figure 2.10: Time windows with deadlock between paths……………………… 28 Figure 2.11: Conflict-free routes …………………………………………………….28 Figure 3.1: Structure of software …………………………………………………….29 Figure 3.2: Five fields of data structure …………………………………………… 29 Figure 3.3: Structure of ID code …………………………………………………… 31 Figure 3.4: Flowchart genera Check code algorithm……………………………… 31 Figure 3.5: Main program flowchart …………………………………………………32 vi List of Figures Figure 3.6: Storage Algorithm Flowchart ……………………………………………33 Figure 3.7: Retrieval Algorithm Flowchart ………………………………………… 34 Chapter 3: EXPERIMENTAL SOFTWARE DEVELOPMENT 3.3 Software Interfacing A simulation environment was built to validate the outcomes of the algorithm The environment has two separate parts a V-REP environment and a MATLAB control center (see Fig 3.9) The V-REP program provides a physical environment to construct a 1:2000 model of the real warehouse The simulation is connected with a MATLAB control UI to oversee all operations Each and every storage cell is properly managed using sensors to verify the availability of the goods in each cell The current states of the warehouse including the time constant of each storage cell and the number of goods inside the warehouse are recorded in MATLAB structures This helps to manage, tracking and control the warehouse operation Fig 3.9 Simulated warehouse layout After selecting the position for the pallets, each pallet is store or retrieve from the appointed location Pallets from different types have different colors MATLAB GUI has three major components:  Warehouse status area: the number of available, filled cells will be continuously updated and displayed  User communication area: includes functions are Storage and Retrieval User need to key in quantity for each type of good need to storage or retrieval at the same time 35 Chapter 3: EXPERIMENTAL SOFTWARE DEVELOPMENT  Display area: when good is added or removed, the coordinate, distance of goods are displayed on area  Warehouse space area: this is 3D space, which include 480 storage location Each cell represents the presence of one pallet in warehouse Color of cells will change when goods are added or removed, conventional colors as shown Fig 3.10 and Fig 3.11  The control of simulation program: includes two buttons: START SIMULATION and STOP SIMULATION for controlling the communication between MATLAB and V-REP and also setting the initial parameters Empty cell A Goods A is filled in B Goods B is filled in C Goods C is filled in D Goods D is filled in E Goods E is filled in F Goods F is filled in Fig 3.10 Color convention of goods Fig 3.11 Warehouse Space 36 Chapter 4: SIMULATED RESULT AND DISCUSSION Chapter 4: SIMULATED RESULT AND DISCUSSION As chapter illustrates, the actual operation of importing and exporting goods in cold warehouse is required to find the shortest path from the buffer to the storage location, in order to save energy and storage time On the other hand, the warehousing process must ensure that no "honeycomb" appear in the warehouse, which means that the warehouse is full but there are still omitted location to cause reducing the efficiency of the warehouse management To evaluate the effectiveness of established algorithms, three comparisons were made based on distance traveled The comparison of determining storage location algorithm shows the improvement of the algorithm from random to ABC, COL, and finally the highest distance saving from the continuous cluster method In addition, a comparison of route planning based on filled volumes helps us to understand the optimal distribution function in the actual storage process 4.1 Travel distance improvement under localization policy Firstly, 64 SKUs of each type of goods were added to system A is came in first, then to B, C, D, E and follow FIFS policy, totally 384 pallets are move in to the system The warehouse layouts under those algorithms are shown in Fig 4.1 and Fig 4.2 Travel distance of each method is shown in Table 4.1 Table 4.1 Travel Distance under Localization Policy (mm) Sequence Continuous Type Random ABC 1-64 A 1894010 1423250 1232300 65-128 B 1792300 1487230 1365720 129-192 C 1903200 1735770 1482390 193-256 D 1816600 1782880 1656320 257-320 E 1893200 1893600 1832600 321-384 F 1882470 2032400 1984520 37 cluster Chapter 4: SIMULATED RESULT AND DISCUSSION Fig 4.1 Warehouse Space under Random Policy Fig 4.2 Warehouse Space under continuous cluster policy Based on data in this table and warehouse space, the impacts of those algorithm could be summarized as follows: In terms of distance, under continuous cluster method, the total travel distance in each period is shorter than randomize and ABC policy distance (see Fig 4.3) But as more and more pallets are entered, the difference in distance between algorithms is shortened 38 Chapter 4: SIMULATED RESULT AND DISCUSSION Fig 4.3 Travel distance under localization policy Fig 4.4 Travel distance improvement under At the 5th import (A5), the distance of the algorithms is almost equal, but in terms of overview, the algorithms have been built with significant efficiency (see Fig 4.4) Under the continuous cluster method with 30% capacity of warehouse, travel distance 39 Chapter 4: SIMULATED RESULT AND DISCUSSION is lower than 29.52% and 8.47% compare with algorithm base on Random and ABC policy respectively This efficiency is maintained at 22.25% and 9.35% when the total stock is filled up 60% The indicator dropped to 14.56% and 7.17% when volume is reached 80% warehouse capacity Several experiments have shown that if the number of SKUs allow to go through warehouse is smaller (the smaller the number of pallet), the efficiency of the continuous cluster algorithm are higher In addition, under continuous cluster method goods were sorted neatly on the clusters, which made the management of goods become more favorable Under random storage policy, goods were sorted messy and lots of the honeycomb loss appear in system (see Fig 4.1) In fact, neat goods arrangements will make handling of goods, maintenance, operation and cleaning easier, especially the periodical inventory audit 4.2 The efficiency of dynamic routing algorithm by travel distance comparison Table is the total time consumption on tasks A, B and C, respectively, through two static and dynamic routing algorithms With dynamic algorithms, two forklift are used in parallel to perform all tasks while in static routing algorithm, the picking up and retrieval process is done by a single vehicle (the travel distance of both cases are the same) Based on data, the dynamic management algorithm is save 21.25% of travel distance at 30% volume is filled When the system is reach 60% capacity, the saving approximately 32.74% compare with static algorithm 27.97% is an improvement of this algorithm when warehouse reach 80% capacity In addition, another optimistic point for dynamic algorithms is the prediction and avoidance of collisions between two vehicles, in the system of cold storage with narrow paths, time consumption is not analyzed since travel distance is most priority, but work avoid collisions between two vehicles and traffic jams help to save time, as well as reduce the risk of accidents 40 Chapter 4: SIMULATED RESULT AND DISCUSSION Table 4.2 Travel distance of static and dynamic routing Dynamic routing(mm) Static routing (mm) Fill up from Fill it up to 60% from Fill up to 85% from 0% volume 35% and then drain it 45% and bring it to 35% (A) down to 45% level (B) down to 50% (C) 2150350 4121000 6217120 2730240 6237300 8631320 Fig 4.5 Travel distance of static and dynamic routing 41 Chapter 5: CONCLUSION & FUTURE WORK Chapter 5: CONCLUSION & FUTURE WORK 5.1 Conclusion Minimizing warehouse operation costs is an important requirement in cold warehouse management It can be done in a variety of ways, such as redesigning warehouse layout, automation with AS / RS, etc But the cost to implement is very high and take the time In this thesis, a new solution is proposed, which is to build the algorithm for managing forklift vehicles in cold warehouse with narrow aisle A builtin program for management which can store name of goods, coordinate, import or out export time of shipment and integrated RFID testing algorithms as well Warehouse space is simulated 3D detailing to each storage location, providing interactive user interface The algorithm is proposed to optimize the travel distance of two forklift vehicles in the space containing 480 storage locations The shortest path is built simultaneously by the optimal storage location determination algorithm in the storage process, and the shortest path planning for the forklift Localization is improved with the A star algorithm combined with the continuous cluster algorithm (advance of the ABC and COL algorithm) Windows time concept is applied to helps avoid collisions between forklift vehicles as well as traffic jams which can caused crippling the system The simulation results show that the continuous cluster and A-star algorithm can save up to 29.52% and 9.35% of the travel distance compared with random and ABC algorithm By optimizing the paths based on the windows time algorithm, the total distance is reduced up to 29.75% compare with static routing (record from simulated scenario in this thesis) In addition, the simulation was not record any collision or deadlock, traffic jams as well By looking at the 3D space simulated of the program, there is not any wasted storage location (honeycomb), so warehouse space is used effectively 42 Chapter 5: CONCLUSION & FUTURE WORK 5.2 Future work Future work will include more complex comparisons such as the quantity of goods are delivered must be greater like the real environment The frequency of storage and retrieval tasks need to higher than so that could validate the stable of the designed system Moreover, mechanical system design to connect with software need to be implement, this is next step to completely build an automated storage and retrieval system in warehouse 43 REFERENCE Chapter 6: REFERENCES [1] Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Development of automated storage and retrieval algorithm in cold warehouse”, South East Asean technical university consortium symposium, 13 -14 March 2017 [2] Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Development and Optimization of Automated Storage and Retrieval Algorithm warehouse by Combining Storage Location Identification and Route Planning Method” IEEE International Conference on System Science and Engineering 2017 [3] Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Building Management Algorithms in Automated Warehouse Using Continuous Cluster Analysis Method” Recent Advances in Electrical Engineering and Related Sciences: Theory and Application, 2017 [4] Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Optimal Dynamic Routing For Forklifts in Narrow-Aisle Racking Warehouse”, International conference on machine, material and mechanical teachnology, IC3MT 2018 [5] Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Optimizing Automated Storage and Retrieval Algorithm in Cold Warehouse by Combining Dynamic Routing and Continuous Cluster Method”, The 5th International Conference on Advanced Engineering - Theory and Applications AETA 2018 [6] Tua Agustinus Tamba, Quyen T T Bui and Keum-Shik Hong, “Trajectory Generation of an Unmanned 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Charles G Petersen, Gerald R Aase, “Improving Order Picking Efficiency with the Use of Cross Aisles and Storage Policies”, Open Journal of Business and Management, 2017, 5, 95-104 [33] A.M Sardha A Dynamic Storage Assignment for a replenishment warehouse, master thesis, Erasmus University Rotterdam, 2017 [34] Antti Pohjalainen Control Policies of an Automated Storage and Retrieval System, Master thesis, Aalto University School of Electrical Engineering, 2015 [35] Faraz Ramtin, Modeling And Analysis Of Automated Storage And Retrieval System With Multiple In-The-Aisle Pick Positions, Master Thesis, 2010 47 APPENDIX APPENDIX International Magazine Truong Ngoc Cuong, Nguyen Duy Anh, Dang Truong Giang, “Development of Automated Storage and Retrieval Algorithm in Cold Warehouse”, SEATUC 2017, OS05, 84, 2017, ISSN: 1882-5796 International Conference - Lecture Note Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Optimizing Automated Storage and Retrieval Algorithm in Cold Warehouse by Combining Dynamic Routing and Continuous Cluster Method”, Lecture Notes in Electrical Engineering of Springer AETA 2018: Recent Advances in Electrical Engineering and Related Sciences, 2018, Ostrava-Poruba - Czech Republic, Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Building Management Algorithms in Automated Warehouse using Continuous Cluster Analysis Method”, Lecture Notes in Electrical Engineering AETA 2017: Recent Advances in Electrical Engineering and Related Sciences: Theory and Application, 2017, Ho Chi Minh - Việt Nam, ISBN: 987-3-319-69813-7, ISSN 1876-1119 (electronic) International Conference Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Optimal Dynamic Routing For Forklifts in Narrow-Aisle Racking Warehouse”, 2018 International Conference on Machining, Materials and Mechanical Technologies (IC3MT), 2018, Ho Chi Minh - Viet Nam, ISBN: 978-604-73-6010-9 Ngoc Cuong Truong, Truong Giang Dang, Duy Anh Nguyen, “Development and Optimization of Automated Storage and Retrieval Algorithm in Warehouse by Combining the Storage Location Identification and Route Planning Method”, IEEE International Conference on System Science and Engineering ( ICSSE 2017 ), 2017, Ho Chi Minh - Viet Nam, ISBN: 978-1-5386-3421-9 48 LÝ LỊCH TRÍCH NGANG LÝ LỊCH TRÍCH NGANG Thơng Tin  Họ tên: Trương Ngọc Cường  Ngày, tháng, năm sinh: 01/02/1994  Nơi sinh: Bà Rịa – Vũng Tàu  Địa liên lạc: 2/92 đường Thiên Phước, phường 9, quận Tân Bình, Tp Hồ Chí Minh Q Trình Đào Tạo  Từ 08/2012 đến 12/2016: sinh viên đại học chuyên ngành Cơ Điện Tử, khoa Cơ Khí, trường Đại học Bách Khoa Tp HCM  Từ 06/2017 đến nay: học viên cao học, chuyên ngành Cơ Điện Tử, khoa Cơ Khí, trường Đại học Bách Khoa Tp HCM Q Trình Cơng Tác Từ 01/2017- nay: Kỹ sư phận Test Process and Equipment, công ty TNHH Intel Products Vietnam, khu Công Nghệ Cao quận 9, Tp.HCM 49 ... thesis Studying and building automated storage and retrieval algorithm in cold warehouse is my own research It is entirely of my own work and has not been submitted to any other college or higher institution,... determining storage location algorithm and path planning in narrow aisle racking system A warehouse layout is designed for 480 storage locations on 16 pallet racking, separated by storage aisles and. .. 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