TRANSFER BATCH PLANNING MODEL IN THE PRODUCTION SCHEDULE

Введение. Данная статья посвящена решению задачи планирования передаточных партий операций на базе данных холдинга «ЛЕНПОЛИГРАФМАШ». Решение задачи планирования передаточных партий актуально, поскольку существующая ситуация «ручного» ввода размерности партий, отсутствие учета окончания партий при планировании ограничивают сокращение времени на производство продукции. Данные и методы. Представленная в работе математическая модель имеет ряд допущений для уменьшения вычислительной сложности рассматриваемой задачи, а также из-за алгоритма планирования. В качестве целевой функции в модели выбрана минимизация начала планирования маршрутной карты. Для решения задачи предложен алгоритм, позволяющий вычислить необходимый размер партии и сопоставление партий предыдущей маршрутной карты со следующей маршрутной картой. Полученные результаты. Апробация предложенного алгоритма проводилась на данных холдинга «ЛЕНПОЛИГРАФМАШ», в информационной системе 1С:MES Оперативное управление производством, редакция 1.3 (далее 1С:MES), что позволило удостовериться в выполнении ограничений при построении графика производства. Заключение. Разработанные модель и алгоритм планирования передаточных партий для внедрения в 1С:MES могут быть использованы на предприятии, позволят эффективнее регулировать загруженность производственного оборудования с учетом передаточных партий и уменьшить срок выполнения заказов. Introduction. This article is devoted to solving the problem of planning transfer batches of operations based on the data of the LENPOLIGRAFMASH holding. The solution of the problem of planning transfer batches is relevant, since the existing situation of "manual" input of the batch size, the lack of consideration of the end of batches in planning limits the reduction of time for production. Data and methods. The mathematical model presented in this paper has a number of assumptions to reduce the computational complexity of the problem under consideration, as well as due to the planning algorithm. The goal function in the model is to minimize the start of route map planning. To solve the problem, an algorithm is proposed that allows calculating the required batch size and comparing the batches of the previous route map with the next route map. Obtained result. Testing of the proposed algorithm was carried out on the data of the LENPOLIGRAFMASH holding, in the information system 1C: MES Operational production management, version 1.3 (hereinafter 1C: MES). this allowed us to make sure that the restrictions were met when building the production schedule. Conclusion. The developed model and algorithm for planning transfer batches for implementation in 1C: MES can be used at the enterprise, will allow you to more effectively regulate the workload of production equipment, taking into account transfer batches, and reduce the order completion time.

570. “I don’t know”: The Typical Response When Taking Pneumococcal Immunization Histories in Kidney Transplant Candidates

Background Vaccine-preventable diseases account for significant morbidity and mortality in the kidney transplant (KT) patient population. AST Guidelines support review and documentation of pneumococcal vaccines in KT candidate infectious disease (ID) evaluations. The objective of this study is to determine the number of KT candidates screened for prior pneumococcal immunizations and the frequency of vaccines ordered by providers when indicated at Mayo Clinic Florida’s (MCF) Transplant Center. Methods This study was an institution-based retrospective analysis of all KT candidates evaluated at MCF from December 2, 2019 – January 14, 2020. Data collection was obtained by electronic health record review. Outcomes included known history and documentation rates of prior pneumococcal vaccinations (both Prevnar 13 and Pneumovax 23) by infectious disease (ID) providers, as well as pneumococcal vaccine order frequency during ID pre-transplant evaluation when indicated. Data analysis was done using simple descriptive statistics. Results Sixty-one patients underwent KT evaluation during the study period. Among the 61 patients, 20 (32.8%) and 20 (32.8%) had a known prior history of receiving Prevnar 13 and Pneumovax 23 vaccinations, respectively. Vaccine history was unknown for Prevnar 13 and Pneumovax 23 in 39 (63.9%) patients. Vaccine status was not documented by ID providers in 2 (3.3%) patients. When appropriate, ID providers ordered Prevnar 13 and Pneumovax 23 in 38 (92.7%) and 41 (100%) patients, respectively. Orders included both electronic and written documentation to account for patients planning immunization elsewhere. Of the 38 patients advised to receive the Prevnar 13 vaccine, 17 (41.5%) patients were documented completing immunization. Pneumovax 23 order completion rates were not recorded since the study period only lasted six weeks due to closure by COVID-19. Table 1. Pneumococcal Vaccine History Documentation Rates Obtained by Patient Recall or Records Table 2. Pneumococcal Vaccine Order Rates at Pre-Kidney Transplant Consultations Table 3. Prevnar 13 Order Completion Rate by Documentation Conclusion The data reflect a high number of patients who either do not recall or have documentation of prior pneumococcal vaccination available at time of KT ID evaluation. Providers documented history of pneumococcal vaccinations extremely well, ordering immunizations when necessary. This study highlights lack of portability of immunization histories in a given patient population and opportunity for improved care. Disclosures Claudia R. Libertin, MD, Pfizer, Inc. (Grant/Research Support, Research Grant or Support)

Data-Driven Modeling and Optimization of the Order Consolidation Problem in E-Warehousing

We analyze data emanating from a major e-commerce warehouse and provided by a third-party warehouse logistics management company to replicate flow diagrams, assess order fulfillment efficiency, identify bottlenecks, and suggest improvement strategies. Without access to actual layouts and process-flow diagrams and purely based on data, we are able to describe the processes in detail and prescribe changes. By investigating the characteristics of orders, the wave-sorting operation, and the order-preparation process, we find that products from different orders are picked in batches for efficiency. Similar products are picked in small containers called totes. Totes are then stored in a buffer area and routed to be emptied of their contents at induction lines. Orders are then consolidated at the put wall, where each order is accumulated in a cubby. This order consolidation process depends on the sequence in which totes are processed and has a huge impact on order-completion time. We, therefore, present a generalization of the parallel machine–scheduling problem that we call the order consolidation problem to determine the tote-processing sequence that minimizes total order completion time. We provide mathematical formulations and devise heuristic and exact solution methods. We propose a fast simulated annealing metaheuristic and a branch-and-price approach in which the subproblems are variants of the single machine-scheduling problem and are solved using dynamic programming. We also devise a new branching rule, compare it against the literature, and test it on randomly generated and industry data. Applied to the data and the warehouse under study, optimizing the order consolidation is found to decrease the completion time of 75.66% of orders and achieve average improvements of up to 28.77% in order consolidation time and 21.92% in cubby usage.

RANCANGAN SISTEM PENDUKUNG KEPUTUSAN UNTUK PENERIMAAN PESANAN PADA PERUSAHAAN MAKE TO ORDER DENGAN MODEL MATEMATIKA OPTIMASI

Manufacturing companies engaged in the system of making orders are now starting to develop with increasingly diverse needs, and the business of making agricultural and food processing machinery is no exception. UD. rekayasa Wangdi W produced the machine processing manufacturing companies engaged in the make to order system are now starting to develop rapidly along with increasingly diverse needs, and the business of making agricultural and food product processing machines is no exception. UD. Wangdi W Engineering is a Make To Order (MTO) manufacturer of processing machines which currently does not consider resource capacity and order due to date as a reference for receiving orders. Even though accepting all orders does not necessarily provide maximum benefits. To help solve these problems, a decision support system design for planning the acceptance of customer orders is carried out. The system is designed using a mathematical model that was developed and modified in linear programming. The model developed has an objective function of maximizing profits from orders received and applied in the system built. The system is designed and the Mathematical Model is processed using the branch and bound method. Based on experimentation with historical data, the results obtained are only 4 slicer and 10 spinner units with a maximum profit of Rp53,115,530.00 and order completion that does not exceed the due date. Order acceptance information is displayed in tabular form and machine scheduling information is displayed in Gantt chart format

Part II Commentary on the International Expedited Rules, 43 Articles E-7 to E-9—The Proceedings Under the Expedited Procedures

This chapter looks at Articles E-7 through E-9 of the ICDR Rules, which set out some basic procedural guidance for an arbitration proceeding the Expedited Procedures once the case has been transferred to the sole arbitrator. These articles grant the arbitrator with discretion to set the procedure and timetable for the arbitration. Unlike the comparable provisions in the main ICDR Rules, however, this provisions presume certain limitations on the procedure to promote the efficiency goals of the Expedited Procedures. Perhaps most notable is the presumption that an expedited arbitration will be decided on documents only, without an oral hearing. Other limitations include time limits on certain procedural benchmarks, such as the issuance of a procedural order, completion of written submissions, and time for an oral hearing, where necessary.

Computer simulation in identification and elimination of waste in the production process

This paper lays the theoretical foundations for the characterisation the course of processes in production engineering by means of computer tools, with the focus on the essence and benefits resulting from the use the programmes in question. The main objective of this study is to employ a selected computer tool for modelling, analysing and simulating a selected product manufacturing process to identify areas in the process that require improvement. The work involved the Tecnomatix Plant Simulation programme, in which the existing production process was modelled. The created model was used to simulate the runtime of the production lot, identify bottlenecks and analyse production losses, such as: waiting, stocks, and unnecessary transport. The conducted analysis has produced an outcome in the form of methods for eliminating identified production losses and modifying the model. The simulations were subsequently carried out on a modified model, which allowed determining the level of improvement of the assumed indicators, e.g. order completion time, set-up time, waiting time, stocks. The selected tool served not only as a means to visualising the course of the manufacturing process but also enabled us to optimise and improve it. The article presents the possibilities of using simulation programmes to identify and eliminate waste in production processes. In addition, the conclusions show not only the results of the simulations but also the most important benefits resulting from the use of this type of tools in production engineering, in particular in lean production management.

Perceiving hope from oncologists and prognostic understanding and treatment planning.

21 Background: Offering hope during prognostic discussions is widely considered essential to the delivery of humane medical care. However, clinicians always offering hope may undermine realism in patients' prognostic understanding and preparation for what lies ahead. We examine how patients’ perceptions of their oncologists as always offering hope, compared to a more tempered sense of hope, relate to prognostic understanding and treatment planning. Methods: Data came from post-scan baseline assessments of an NCI funded multi-site study on prognostic communication among metastatic cancer patients’ refractory to at least one chemotherapy regimen. The analytic sample consisted of 235 participants, who during structured interviews, rated the question, “how often does your oncologist offer hope,” as “always,” “most of the time” or “sometimes.” A binary variable was created comparing participants endorsing “always” to participants endorsing “most of the time” or “sometimes.” Patients also reported on elements of prognostic understanding, DNR order completion, and preference for either life-extending or comfort care. Results: Patients who rated their oncologists as “always” offering hope (62.1%), compared to those who rated “most of the time” or “sometimes” (37.9%), were more likely to have inaccurate prognostic understanding regarding life-expectancy ( OR = 0.40; 95% CI, 0.16, 0.97), and marginally more likely to have a treatment preference that favored life-extending care over comfort care ( OR = 0.61; 95% CI, 0.35, 1.07). A significant moderation effect was seen ( b = -1.43, p = .04) such that accurate understanding of the incurability of their cancer was associated with DNR completion only among patients who perceived more tempered hope from oncologists ( OR = 5.53; 95% CI, 1.80, 17.02), and not among patients who always perceived hope ( OR = 1.32; 95% CI, 0.63, 2.78). Conclusions: Results suggest that the tempering of hope may have benefits, as perceiving oncologists as always offering hope was associated with worse prognostic understanding and lower advance care planning. Future research examining in a more nuanced way the nature of hope offered (e.g., hope for cure vs. symptom management) in longitudinal designs is needed.