A machine learning approach for predictive warehouse design

Warehouse management systems (WMS) track warehousing and picking operations, generating a huge volumes of data quantified in millions to billions of records. Logistic operators incur significant costs to maintain these IT systems, without actively mining the collected data to monitor their business processes, smooth the warehousing flows, and support the strategic decisions. This study explores the impact of tracing data beyond the simple traceability purpose. We aim at supporting the strategic design of a warehousing system by training classifiers that can predict the storage technology (ST), the material handling system (MHS), the storage allocation strategy (SAS), and the picking policy (PP) of a storage system. We introduce the definition of a learning table, whose attributes are benchmarking metrics applicable to any storage system. Then, we investigate how the availability of data in the warehouse management system (i.e. varying the number of attributes of the learning table) affects the accuracy of the predictions. To validate the approach, we illustrate a generalisable case study which collects data from sixteen different real companies belonging to different industrial sectors (automotive, manufacturing, food and beverage, cosmetics and publishing) and different players (distribution centres and third-party logistic providers). The benchmarking metrics are applied and used to generate learning tables with varying number of attributes. A bunch of classifiers is used to identify the crucial input data attributes in the prediction of ST, MHS, SAS, and PP. The managerial relevance of the data-driven methodology for warehouse design is showcased for 3PL providers experiencing a fast rotation of the SKUs stored in their storage systems

One swallow doesn’t make a summer: reply to Kataria

In this paper we reply to Mitesh Kataria’s comment, which criticized the simulations of Maniadis, Tufano, and List (2014, Am. Econ. Rev.104(1), 277-290). We view these simulations as a means to illustrating the fact that we economists are unaware of the value of key variables that determine the credibility of our own empirical findings. Such variables include priors (i.e., the pre-study probability that a tested phenomenon is true) and the statistical power of the empirical design. Economists should not hesitate to use Bayesian tools and meta-analysis in order to quantify what we know about these variables

One swallow doesn’t make a summer: reply to Kataria

In this paper we reply to Mitesh Kataria’s comment, which criticized the simulations of Maniadis, Tufano, and List (2014, Am. Econ. Rev.104(1), 277-290). We view these simulations as a means to illustrating the fact that we economists are unaware of the value of key variables that determine the credibility of our own empirical findings. Such variables include priors (i.e., the pre-study probability that a tested phenomenon is true) and the statistical power of the empirical design. Economists should not hesitate to use Bayesian tools and meta-analysis in order to quantify what we know about these variables

Can Gambling Increase Savings? Empirical Evidence on Prize-Linked Savings Accounts

This paper studies the adoption and impact of prize-linked savings (PLS) accounts, which offer random, lottery-like payouts to individual account holders in lieu of interest. Using micro-level data from a bank offering these products in South Africa, we show that a PLS product was attractive to a broad group of individuals, across all age, race, and income levels. Financially-constrained individuals and those with no other deposit accounts were particularly likely to open a PLS account. Participants in the PLS program increased their total savings on average by 1% of annual income, a 38% increase from the mean level of savings. Deposits in PLS did not appear to cannibalize same-bank savings in standard savings products. Instead, PLS appears to serve as a substitute for lottery gambling. Exploiting the random assignment of prizes, we also present evidence that prize winners increase their investment in PLS, sometimes by more than the amount of the prize won, and that large prizes generate a local “buzz” which lead to an 11.6% increase in demand for PLS at a winning branch

Preventing postsurgical venous thromboembolism: pharmacological approaches

The use of antithrombotic drugs for the prevention of venous thromboembolism (VTE) in patients undergoing surgery is presently based on solid principles and high-level scientific evidence. This article reviews current strategies of pharmacological thromboprophylaxis. The level of VTE risk following surgery depends on a variety of factors that the surgeon should take into account, including the type of surgery and the presence of additional risk factors, such as elderly age and cancer. In patients undergoing minor general surgery, early mobilization is sufficient as prophylaxis, whereas in those undergoing major general surgery, thromboprophylaxis with low molecular weight heparin (LMWH), low-dose unfractionated heparin, or the pentasaccharide fondaparinux is recommended. Patients undergoing major orthopedic surgery have a particularly high risk of VTE, and routine thromboprophylaxis with LMWH, fondaparinux, or a vitamin K antagonist (international normalized ratio target: 2.0 to 3.0) is the standard of care in this group of patients. Recently, two new oral anticoagulants, rivaroxaban (a factor Xa inhibitor) and dabigatran etexilate (a direct thrombin inhibitor) have been licensed to be used for thromboprophylaxis after orthopedic surgery in Europe. Mechanical methods of thromboprophylaxis (compression stockings, intermittent pneumatic compression, vena cava filters), not discussed in detail in this review, should always be considered in patients at high thrombotic risk, in association with the pharmacolocical strategies, or in cases of contraindications to antocoagulants, as in patients or procedures at high risk of bleeding

Effects of dopamine infusion on forearm blood flow in critical patients.

Piazza O, Zito G, Valente A, Tufano R. Effects of dopamine infusion on forearm blood flow in critical patients. Med Sci Monit. 2006 Feb;12(2):CR90-3. Epub 2006 Jan 26

a tailored maintenance management system to control spare parts life cycle

Abstract The maintenance of complex production systems became increasingly crucial to ensure the competitiveness of companies and service level to their clients. Because of product customization the number of mechanical and electrical components and functional groups of manufacturing lines enhanced with their complexity. To face this concern, the physical and logical design of such systems is typically partitioned among several groups of engineers and designers. Consequently, a holistic awareness of the whole project is lacking and the maintenance of such systems becomes even more challenging. In view of this, new tailored support-decision tools able to manage and control the life cycle of spare parts from their design, throughout the run time, and to their failure and replacement are necessary. This paper illustrates an original maintenance management system (MMS) resulting by the combination of different computerized tools able to integrate the information flow behind the life cycle of a generic component. The proposed system supports coordination among groups of engineers and practitioners through graphic user interfaces (GUIs) and performance i.e. cost, reliability, dashboards, which lead decision-making from the design phase to the planning of maintenance tasks along the life of the manufacturing line. These tools are validated with a real-world instance from the tobacco industry which allows assessing how components belonging to the same functional group may differently behave over their life cycle. The results suggest that the holistic awareness on the whole manufacturing system provided by the proposed MMS can support task design and schedule of maintenance actions providing the reduction of more than 20% of the total cost and time for maintenance actions. The practical example shown contributes to shed light on the potentials of new paradigms for maintenance management in the industry 4.0

Spatial and temporal expression profiling of cell-wall invertase genes during early development in hybrid poplar

Cell-wall invertase genes are spatially and temporally regulated in several plant species, including Daucus carota L., Lycopersicon esculentum L. and Solanum tuberosum L. However, few studies of cell-wall invertase genes of trees have been conducted, despite the importance of trees as a source of lignocellulosic biopolymers.We identified three putative cell-wall invertase genes in hybrid poplar (Populus alba L. × grandidentata Michx.) that showed higher homology to each other than to cell-wall invertases of other dicotyledonous species, with two of the genes (Pa×gINV2 and Pa×gINV3) appearing as a genomic tandem repeat. These genes are more similar to each other than to tandemly repeated cell-wall invertases of other plants, perhaps indicating parallel evolution of a duplication event with cell-wall invertases in dicotyledons. Spatial and temporal expression analyses throughout a complete annual cycle indicated that Pa×gINV1 and Pa×gINV2 are highly regulated in vegetative tissues during three distinct growth phases: early growth, dormancy and post-dormancy. Expression of the third gene (Pa×gINV3) appears to be tightly regulated and may represent a floral-specific cell-wall invertase. Of the two genes expressed in vegetative tissues, Pa×gINV1 appears to be exclusively involved in processes related to dormancy, whereas Pa×gINV2 appears to encode an enzyme involved in phloem unloading and in providing actively growing tissues, such as developing xylem, with the energy and carbon skeletons necessary for respiration and cell wall biosynthesis

an application of collaborative robots in a food production facility

Abstract Despite the food industry being a leading sector of the European economy, the level of penetration of automation is still low. The main reasons lie on the small margin of food items which does not encourage technological investments, the extremely spread vendors market i.e. mostly small and medium enterprises, and the high level of flexibility and care required to handle food products along production, packaging, and storage operations. Nevertheless, the advent of collaborative, small and flexible robots provides great opportunities for the design and development of new effective processes integrating the human flexibility with the efficiency of automation. This paper explores the impact of adopting collaborative robots in the food catering industry, by illustrating a case study developed for the end-of-line of a catering production system. A generalizable methodology is proposed to support the study of the technical and economic feasibility of the implementation of such technology. This methodology is intended to support managers of the food industry to analyse the constraints that limit the automation of a process and to measure the expected performance of the system in terms of throughput, ergonomics and economic benefits resulting from the adoption of collaborative robots