6 research outputs found
Decision support models and policy innovations to support automating store fulfillment
No full textDecember 2024School of EngineeringOmnichannel services, such as buy-online-pickup-in-store, curbside pickup, and ship-from-store, have shifted the order-picking tasks that used to be completed by in-store customers doing their own shopping to the responsibility of retailers. To support research on omnichannel serivces,relevant connected in-store and online customer data sets for omnichannel retail research are generated via a mapped categorization of products into product families. Using this mapping to connect previously separate in-store and online customer data sets, these data sets focus on a grocery retail environment, and collect additional data from publicly available websites. These connected data sets contain information about product family data on in-store and online customer demand values, impulse purchases, product dimensions, weight, and price. Additional data is provided on in-store and online customer arrival data. These data sets aid this work in generating numerical insights and can support future grocery retail logistical research. To support omnichannel services, many retailers have deployed a store fulfillment strategy, where online orders are picked from inventory in brick-and-mortar stores. As store fulfillment is currently a labor-intensive operation, this dissertation explores a new policy that relies on the assistance of in-store customers for item extraction from the store shelves and a fleet of Autonomous Mobile Robots (AMRs) to collect and transport them to a designated station. While a set of dedicated pickers and AMRs are manageable by the store, the arrival of in-store customers who are willing to assist an AMR at a given location in the store is out of the store's control, and therefore, uncertain. We model the stochastic order-picking problem with uncertain synchronization times of in-store customers and AMRs, first as a static approach via generating a consensus from multiple scenarios and decisions to visit picking locations are made at the beginning of the picking journey. Then we consider managing resources in a dynamic way, where the store makes new decisions as new information becomes available. We model the dynamic problem as a Markov Decision Process to determine how a retailer should dynamically assign tasks to a set of AMRs and dedicated pickers. We develop a heuristic solution framework that generates a set of initial assignments and routes for picking resources and dynamically updates them as the actual synchronization times between AMRs and in-store customers unfold. We analyze multiple strategies to generate the initial set of task assignments and routes as well as update such decisions based on the system state. We test our proposed approaches using actual online grocery data. Computational results illustrate the potential for AMRs and in-store customers augmenting the dedicated pickers to achieve equivalent pick rates compared to systems with only dedicated pickers. We further demonstrate that it is more effective for achieving higher picking performance to have in-store customers help the AMRs compared to a warehouse like environment where dedicated pickers are synchronized with AMRs. Moreover, our proposed policy improves the operating margin of the store compared to utilizing only dedicated pickers. Lastly, our solution approach is capable of generating high-quality solutions at a pace suitable for practical settings. In addition to fulfilling online customer requests, omnichannel retailers also must support in-store customers, who want to interact with products and often drive sales through impulse purchases and customer loyalty. Yet, how best to support both online and in-store customer channels efficiently and seamlessly is a current challenge for retailers. Thus, the second focus of this work is to explore whether new material handling equipment has the potential to be deployed in a retail store environment to support omnichannel services. To do so, we utilize pick performance data from a newly designed and built picker-to-stock robotic platform suitable for piece-level pick, sort, and place tasks in retail environments. Then an agent-based simulation model is created to mimic a store's logistical operations that integrates data from the robotic platform's lab demonstrations and data from online and in-store customer demand. An iterative process determines the minimum amount of manual and robotic resources needed to operate the store that satisfies a given service level for online order fulfillment and replenishment tasks. Then, to assess the economic viability of deploying such a robotic platform with currently achieved values and improved performance, these resource levels are combined with operational metrics obtained from the simulation and various cost aspects via an economic analysis model. Computational experiments show that deploying the robotic platform for picking and restocking goods in a store environment is operationally and economically viable for retail grocery stores providing omnichannel services using a store fulfillment strategy.Ph
Perspectives on Automation for Omnichannel Services and the Need for New Robotic Solutions for Store Fulfillment Operations
No full textAssessing economic and operational feasibility of a designed and lab demonstrated robotic platform for omnichannel logistics
No full textProspective on Automation for Omnichannel Services and the Need for New Robotic Solutions for Store Fulfillment Operations
No full textAs businesses offer omnichannel services, such as buy-online-pickup-in-store, more logistical processes need to be conducted within or close to a retail environment. For retailers who adopt a store fulfillment concept, order picking for online orders is conducted inside a store environment and is in addition to the logistic processes required to support in-store customer requests. A store fulfillment approach has the advantage of enabling inventory, labor, infrastructure, and automation to be pooled for online orders, in-store customers, and return processing. Yet, the design and operation of logistical tasks completed in a retail environment is more challenging and requires considering the salient features that vary from a distribution environment. This work provides an overview of omnichannel logistical processes and connects their unique features to open challenges in automating these processes. A benchmarking and classification study describes the state of the practice in 2022 in automated picking solutions. We find that the current market for automated picking solutions that could support a microfulfillment strategy is more mature than solutions that could support a store fulfillment strategy. We identify a set of design and technical requirements for an automated picking solution deployed in a retail environment to support store fulfillment. Moveable robotic piece-level picking solutions need to become more flexible so that they can accommodate different item types, store shelf designs, facility layouts, logistical tasks, and human interactions, as well as more agile so they can robustly operate in uncertain and new environments
The dimensional evolution of structure and dynamics in hard sphere liquids
No full textThe formulation of the mean-field infinite-dimensional solution of hard sphere glasses is a significant milestone for theoretical physics. How relevant this description might be for understanding low-dimensional glass-forming liquids, however, remains unclear. These liquids indeed exhibit a complex interplay between structure and dynamics, and the importance of this interplay might only slowly diminish as dimension d increases. A careful numerical assessment of the matter has long been hindered by the exponential increase in computational costs with d. By revisiting a once common simulation technique involving the use of periodic boundary conditions modeled on Dd lattices, we here partly sidestep this difficulty, thus allowing the study of hard sphere liquids up to d = 13. Parallel efforts by Mangeat and Zamponi [Phys. Rev. E 93, 012609 (2016)] have expanded the mean-field description of glasses to finite d by leveraging the standard liquid-state theory and, thus, help bridge the gap from the other direction. The relatively smooth evolution of both the structure and dynamics across the d gap allows us to relate the two approaches and to identify some of the missing features that a finite-d theory of glasses might hope to include to achieve near quantitative agreement. © 2022 Author(s)
Odontotrypes (Odontotrupes) tawangensis Gupta, Chandra & Hillert, 2016, new species
No full text<i>Odontotrypes</i> (<i>Odontotrupes</i>) <i>tawangensis</i> new species <p>(Figs. 1–19)</p> <p> <b>Type locality.</b> India, Arunachal Pradesh state, Tawang district.</p> <p> <b>Type material.</b> 18 specimens: holotype male labeled: “ India, Arunachal Pradesh state, Tawang district / Sela / 27.523491N, 92.106493E / 5.x.2010 / collected K. Chandra ” in ZSCI [ZSI Registration Number: 21489/H4A]. Allotype female labeled: “NE INDIA W, ARUNACHAL PR / TAWANG Monastery vicinity / 27°35´30´´N 91°51´E; 2700–3000 m / 19.-27.v. 2004 ” in SJCP. Paratypes: “ India, Arunachal Pradesh state / Tawang district / Sela 27.523491N, 92.106493E / 5.x.2010 / collected K. Chandra ” 1 male in ZSCI [ZSI Registration Number: 21490/H4A]; “NE INDIA W, ARUNACHAL PR / TAWANG Monastery vicinity / 27°35´30´´N 91°51´E; 2700– 3000 m / 19.-27.v. 2004 ” 1 male in DKCP, 1 male and 1 female in JSCP, 6 males and 4 females in SJCP, 1 male and 1 female in OHCB.</p> <p> <b>Description of holotype</b> (Fig. 1). Length 20.0 mm, maximum width 9.7 mm, oblong and convex. Dorsally black; vertex and elytra at base with metallic luster; ventral surface black with cuprous tinge especially on mesofemora, metafemora, and anterior part of pronotum.</p> <p>Head (Figs. 2, 4): Labrum truncate anteriorly. Anterior clypeal margin broadly arcuate, clypeal disc distinctly elevated in middle, clypeal surface slightly rugopunctate near lateral margins, elevated areas smooth; area around frontoclypeal junction distinctly depressed, T-shaped, suture distinct. Median suture on vertex indistinct; eye tubercle blunt and distinctly prominent dorsally, in lateral view angular; eye canthus smooth.</p> <p>Pronotum (Figs. 3, 5): Transverse, broadest just posteriad of middle; completely bordered (finely at base); lateral margins rounded, not crenulate; anterior marginal carina moderately elevated and widened in middle. Anterior angles blunt, broadly rounded, sides almost straight in anterior third forming a rounded lateral angle; posterior angles bent 45°. Surface completely smooth in middle with few scattered punctures; anterior concavity reduced, simple depression; lateral fovea small with rugopunctation; surface near lateral margins rugopunctate anteriorly and posteriorly.</p> <p>Scutellum (Fig. 7): Pentagonal, basal margin not bordered, slightly declined inward, surface entirely smooth, yellow border present at each side from meeting point to base.</p> <p>Elytra (Fig. 6): Humeral umbone weakly prominent; base almost equal in length to pronotum, neither margined nor carinate; surface glabrous. Surface with 7 distinct striae clearly indicated between suture and humeral umbone, which gradually disappear towards apex; intervals 3–7 convex and impunctate; lateral side with a continuous carina from humeral umbone to apex.</p> <p>Legs (Figs. 8–9): Profemora black, not shiny, completely smooth; mesofemora and metafemora shiny with 2 rows of setose punctures. Protibiae laterally with 5 teeth including 4 distinct anterior teeth, and 1 weak basal tooth (Fig. 8); on ventral side medially with 7 teeth including 3 anterior, sharp, distinct teeth and 4 blunt, reduced teeth (Fig 9).</p> <p>Macropterous (Fig. 10).</p> <p>Abdominal ventrites shiny, serrate punctate.</p> <p>Aedeagus as in Figs. 11–13 (holotype) and 16–17 (paratypes: India, Arunachal Pradesh, Tawang Monastery vicinity, in DKCP).</p> <p>Measurements (mm): Median length of head (excluding labrum and mandibles) 3.1, distance between frontal tubercles 2.9, anterior margin of clypeus (circumference) 4.1, median length of pronotum (dorsal) 5.3, maximum width 9.6, median length of scutellum 1.3, maximum width 1.7, sutural length of elytra (dorsal) 9.2, maximum width combined 9.7, aedeagus (length) 3.7.</p> <p> <b>Variation</b>. Length 17.0–20.0 mm, width 8.5–9.7 mm. The female differs from male by the less developed clypeal tubercle and the weaker protibial teeth.</p> <p> <b>Distribution</b>. Only known from type locality: Sela, Tawang, Arunachal Pradesh, India (Fig. 15).</p> <p> <b>Etymology.</b> The name <i>tawangensis</i> refers to the type locality of this species, the Tawang district of the state of Arunachal Pradesh.</p> <p> <b>Differential diagnosis.</b> <i>Odontotrypes</i> (<i>Odontotrupes</i>) <i>tawangensis</i> new species is distinguished from the closely related species <i>O</i>. (<i>O</i>.) <i>orichalceus</i> (reported from the Tibetan Plateau of Sikkim) by the unique structure of the aedeagus (Figs. 11–13, 16–17) (right paramere with distinct internal truncate appendix situated subapically and directed inward) and the structure of the elytra (elytral striae are distinct basally, becoming more shallowly apically), and the well-developed metathoracic wings. Based on the keys given by Král <i>et al.</i> (2001) <i>Odontotrypes</i> (<i>O.</i>) <i>tawangensis</i> should be classified in the subgenus <i>Odontotrupes</i>. Species of this subgenus that are distributed in Bhutan and India characteristically have slightly reduced or normal-sized metathoracic wings, namely <i>O.</i> (<i>O.</i>) <i>bhutan</i>, <i>O.</i> (<i>O.</i>) <i>gogona</i>, <i>O.</i> (<i>O.</i>) <i>orichalceus</i>, and <i>O.</i> (<i>O.</i>) <i>tawangensis</i>. According to Král <i>et al.</i> (2001) the distribution ranges of <i>Odontotrypes</i> are relatively small, many of them being endemic to single mountain systems, separated by deep river valleys.</p> <p>The authors wish to thank the director of the Zoological Survey of India, for providing them with the necessary facilities and for his encouragements. The first author is thankful to Paul Schoolmeesters (Belgium) for literature, Baiju Lal (former Officer-in-Charge, Coleoptera Section, Zoological Survey of India), Amitava Mujumder, and Joyjit Ghosh. We also thank Marc Miquel (Queen Mary University of London, United Kingdom) for editing our English text and review the earlier version of manuscript and Stanley Jákl, David Král, and Jan Schneider for access to the specimens examined.</p>Published as part of <i>Gupta, Devanshu, Chandra, Kailash & Hillert, Oliver, 2016, Odontotrypes (Odontotrupes) tawangensis new species (Coleoptera: Geotrupidae) from Arunachal Pradesh, India, pp. 559-566 in Zootaxa 4154 (5)</i> on pages 560-565, DOI: 10.11646/zootaxa.4154.5.4, <a href="http://zenodo.org/record/264799">http://zenodo.org/record/264799</a>
