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Robotic Warehouses for E-Commerce: Evaluation, Operation, and Design
Robotic Warehouses for E-Commerce: Evaluation, Operation, and Design
Robotic Warehouses for E-Commerce: Evaluation, Operation, and Design

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20250211151332
ISBN  
9798384448457
DDC  
385
저자명  
Huang, Yiduo.
서명/저자  
Robotic Warehouses for E-Commerce: Evaluation, Operation, and Design
발행사항  
[Sl] : University of California, Berkeley, 2024
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2024
형태사항  
108 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-04, Section: B.
주기사항  
Advisor: Shen, Zuo-Jun.
학위논문주기  
Thesis (Ph.D.)--University of California, Berkeley, 2024.
초록/해제  
요약As e-commerce expands, warehouse systems face new challenges, leading to the development of robotic warehouses. These warehouses typically employ part-to-picker systems, where mobile robots and stationary human workers collaborate. To improve the performance of these systems, we proposed new performance evaluation models and operational strategies. We also proposed innovative designs aimed at fully robotic warehouses in the foreseeable future.Performance prediction and evaluation are crucial in designing and operating robotic warehouses, especially given the highly stochastic and complex nature of robot traffic congestion. We introduced a new evaluation model that accounts for robot congestion by initially modeling the system as a closed queueing network (CQN) with blocking. Simulation observations led us to propose a congestion mechanism and simplify the system to a CQN without blocking. Demonstrating the asymptotic Poisson properties of robot arrivals enabled us to further approximate the simplified CQN as a transportation network. This approach allowed us to estimate congestion delays as closed-form functions of traffic flow. We integrated these estimated delays with the CQN model and developed an iterative algorithm to estimate the system throughput. Our numerical experiments confirmed that this method could accurately predict throughput under transportation congestion when the system was stable.Effective real-time robotic warehouse operation requires strategic decisions regarding workstation assignments and collision-free robot path planning. To improve system efficiency, we developed an integrated method for task assignment and path planning, implemented in both offline and online phases. In the offline phase, based on our evaluation model, we estimated an approximated optimal steady-state traffic assignment, while the online phase guided robots according to offline traffic patterns using a decentralized and computationally efficient algorithm. The simulation results indicated that our method achieved 5-10% higher throughput and required much less computational time compared to current industrial implementations.The advent of robotic arms has made fully robotic warehouses feasible. We proposed a new layout design that positions workstations, called internal workstations, equipped with robotic arms within the storage area to minimize transportation costs. We introduced a batching pool mechanism using special pods to collect and transport assembled totes in batches from internal to external workstations. This system was evaluated using an open queueing network (OQN), which led to a closed-form queue delay approximation. We found an upper bound for the relative error in the sojourn time estimation using this approximation and showed that our approximation is accurate. Using this approximation, we developed a location-allocation-queuing model, which can be transformed into mixed integer second-order conic programming (MISOCP) for efficient solving, to find the optimal workstation locations and pod-to-workstation allocation plans. This model demonstrated a significant reduction in transportation costs and an improvement in the robot machine time of 10-20% for large or deep systems in our simulations.
일반주제명  
Transportation
일반주제명  
Industrial engineering
일반주제명  
Robotics
일반주제명  
Environmental engineering
키워드  
Location-queuing model
키워드  
Multi-robot path-planning
키워드  
Queueing system
키워드  
Robot task assignment
키워드  
Robotic warehouses
키워드  
Warehouse layout design
기타저자  
University of California, Berkeley Civil and Environmental Engineering
기본자료저록  
Dissertations Abstracts International. 86-04B.
전자적 위치 및 접속  
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MARC

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■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a385
■1001  ▼aHuang,  Yiduo.
■24510▼aRobotic  Warehouses  for  E-Commerce:  Evaluation,  Operation,  and  Design
■260    ▼a[Sl]▼bUniversity  of  California,  Berkeley▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a108  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-04,  Section:  B.
■500    ▼aAdvisor:  Shen,  Zuo-Jun.
■5021  ▼aThesis  (Ph.D.)--University  of  California,  Berkeley,  2024.
■520    ▼aAs  e-commerce  expands,  warehouse  systems  face  new  challenges,  leading  to  the  development  of  robotic  warehouses.  These  warehouses  typically  employ  part-to-picker  systems,  where  mobile  robots  and  stationary  human  workers  collaborate.  To  improve  the  performance  of  these  systems,  we  proposed  new  performance  evaluation  models  and  operational  strategies.  We  also  proposed  innovative  designs  aimed  at  fully  robotic  warehouses  in  the  foreseeable  future.Performance  prediction  and  evaluation  are  crucial  in  designing  and  operating  robotic  warehouses,  especially  given  the  highly  stochastic  and  complex  nature  of  robot  traffic  congestion.  We  introduced  a  new  evaluation  model  that  accounts  for  robot  congestion  by  initially  modeling  the  system  as  a  closed  queueing  network  (CQN)  with  blocking.  Simulation  observations  led  us  to  propose  a  congestion  mechanism  and  simplify  the  system  to  a  CQN  without  blocking.  Demonstrating  the  asymptotic  Poisson  properties  of  robot  arrivals  enabled  us  to  further  approximate  the  simplified  CQN  as  a  transportation  network.  This  approach  allowed  us  to  estimate  congestion  delays  as  closed-form  functions  of  traffic  flow.  We  integrated  these  estimated  delays  with  the  CQN  model  and  developed  an  iterative  algorithm  to  estimate  the  system  throughput.  Our  numerical  experiments  confirmed  that  this  method  could  accurately  predict  throughput  under  transportation  congestion  when  the  system  was  stable.Effective  real-time  robotic  warehouse  operation  requires  strategic  decisions  regarding  workstation  assignments  and  collision-free  robot  path  planning.  To  improve  system  efficiency,  we  developed  an  integrated  method  for  task  assignment  and  path  planning,  implemented  in  both  offline  and  online  phases.  In  the  offline  phase,  based  on  our  evaluation  model,  we  estimated  an  approximated  optimal  steady-state  traffic  assignment,  while  the  online  phase  guided  robots  according  to  offline  traffic  patterns  using  a  decentralized  and  computationally  efficient  algorithm.  The  simulation  results  indicated  that  our  method  achieved  5-10%  higher  throughput  and  required  much  less  computational  time  compared  to  current  industrial  implementations.The  advent  of  robotic  arms  has  made  fully  robotic  warehouses  feasible.  We  proposed  a  new  layout  design  that  positions  workstations,  called  internal  workstations,  equipped  with  robotic  arms  within  the  storage  area  to  minimize  transportation  costs.  We  introduced  a  batching  pool  mechanism  using  special  pods  to  collect  and  transport  assembled  totes  in  batches  from  internal  to  external  workstations.  This  system  was  evaluated  using  an  open  queueing  network  (OQN),  which  led  to  a  closed-form  queue  delay  approximation.  We  found  an  upper  bound  for  the  relative  error  in  the  sojourn  time  estimation  using  this  approximation  and  showed  that  our  approximation  is  accurate.  Using  this  approximation,  we  developed  a  location-allocation-queuing  model,  which  can  be  transformed  into  mixed  integer  second-order  conic  programming  (MISOCP)  for  efficient  solving,  to  find  the  optimal  workstation  locations  and  pod-to-workstation  allocation  plans.  This  model  demonstrated  a  significant  reduction  in  transportation  costs  and  an  improvement  in  the  robot  machine  time  of  10-20%  for  large  or  deep  systems  in  our  simulations.
■590    ▼aSchool  code:  0028.
■650  4▼aTransportation
■650  4▼aIndustrial  engineering
■650  4▼aRobotics
■650  4▼aEnvironmental  engineering
■653    ▼aLocation-queuing  model
■653    ▼aMulti-robot  path-planning
■653    ▼aQueueing  system
■653    ▼aRobot  task  assignment
■653    ▼aRobotic  warehouses
■653    ▼aWarehouse  layout  design
■690    ▼a0709
■690    ▼a0796
■690    ▼a0546
■690    ▼a0771
■690    ▼a0775
■71020▼aUniversity  of  California,  Berkeley▼bCivil  and  Environmental  Engineering.
■7730  ▼tDissertations  Abstracts  International▼g86-04B.
■790    ▼a0028
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17161269▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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