Optimizing the inventorying and distribution of chemical fluids: An innovative nested column generation approach

Vendor-managed-inventory is a successful business practices based on the cooperation between a supplier and its customers in which demand and inventory information from the customers are shared with the supplier. This practice is gaining popularity in the chemical industry and relies on the inventory-routing-problem, which integrates inventory management, vehicle routing, and delivery scheduling decisions. This one is a difficult combinatorial optimization problem both theoretically and practically. However, because of the large expenses involved in distribution and inventorying of chemical products, it is attractive to make use of optimization tools for exploiting as many degrees of freedom as possible with the goal of minimizing both distribution and inventorying costs. Consequently, we propose a nested column generation algorithm for solving an inventorying and distribution problem that models the delivery of several chemicals fluids. The approach is building on a column generation & incomplete branch-and-price algorithm in which for each delivery route, the delivery patterns of fluids are also determined by column generation. We detail the implementation and provide computational results for realistic test instances.Fil: Coccola, Mariana Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

An enhanced framework for blood supply chain risk management

A blood supply chain (BSC) is a very long and complex sequence of processes heavily sequential. If one of them is executed in an incorrect way and this error is not detected, it leads to an incorrect transfusion outcome, that could seriously affect patients. For this reason, there is a strong need to identify and prevent adverse events along the entire BSC, in order to reduce their probability of occurrence. This also helps improving BSC sustainability from both the environmental and the social perspectives. The paper extends an existing healthcare supply chain risk management framework already applied to the blood transfusion process to address multiple BSC echelons and identify the cause and effect relationships among the adverse events that might occur. To this end, Fault Tree Analysis is added to the risk management tools part of the original framework as well as Key Performance Indicators are applied to detect risky event manifestation. The first application of the proposed approach to a blood bank and a hospital ward revealed its effectiveness in identifying the BSC activities most subjected to risk. Also, connections between adverse events and causal relationships among their sources were found, leading to understanding whether an adverse event is caused by a risk source in the same echelon where it occurs or by the concurrent manifestation of several adverse events upstream in the BSC. Future research will be devoted to numerically evaluate probability of occurrence and impact of risky events as well as integrating the framework with a classification of criticalities based on their severity

Optimization of Fixed Assets Management in Oksibil Regional General Hospital, Pegunungan Bintang Regency, Papua Province

Background: The Oksibil Regional General Hospital is the only government hospital with class D type in the Pegunungan Bintang Regency of Papua Province that is required to provide optimal health services. However, the barriers encountered by Okisibil Regional Hospital Fixed Assets have not been properly managed so as to have an impact on health service providers. The demand for quality of service can not be separated from changes in the environment that are so complex that health services must be proactive and always think about ways to adapt and overcome them. Fixed Asset Management at Oksibil Hospital consists of a series of planning, budgeting, procurement, use, security, maintenance and administration activities. Research Objectives: Reviewing the optimization of Fixed Asset Management at the Oksibil Regional General Hospital, Pegunungan Bintang Regency, Papua Province. Research method: The research method used in this study was qualitatively descriptive with a survey conducted in March-April 2020 at Oksibil Regional General Hospital, Pegunungan Bintang Regency, Papua Province. 8 (eight) informants were taken using a purposive method of sampling. Data obtained from in-depth interviews as primary data and also from secondary data available at Oksibil Hospital. Results: The planning of fixed assets has involved all service units. Fixed asset budgeting was still limited by regional capacity. The use of fixed assets, especially medical equipment, was still limited, only a few buildings have been used, such as HCU, Radiology. Fixed assets were secured by a fence, but there was no warehouse, no registration code and labeling. Maintenance of fixed assets in a planned and unplanned manner was constrained by budgetary constraints. Fixed asset management administration was the sole responsibility of the goods manager, not all units were involved in the inventory and reporting of fixed assets

Developing Improvement Strategy To Increase Logistics Service Quality And Mitigate Risks In PT. Tiga Permata Logistik And PT. Tiga Permata Ekspres

Recently, the growth of business value of 3PL in Indonesia increases from year to year. It can be seen from the growth of 15% of 3PL value business in 2014, which equals to US$170 billion from the previous year, 2013, which has reached US$ 150 billion or equals to IDR 1,772 trillion (Asosiasi Logistik Indonesia, 2014). As the business, trading, production are growing, the needs of 3PL are also increasing. 3PL industries are faced with the growing interest in their services, thus they have to deal with the increased competition as well. They compete to serve the best logistics service quality to attract and grab more customers. It has become a concern for 3PL or logistics service provider to improve the logistics service quality and to increase the competitiveness. Improving the logistics service quality does not only aim to get more profit, but also to engage more with the customers, to satisfy and to increase the loyalty of the customers. With this strategy, a 3PL company can be more sustain in the competition. Besides trying to increase the competitiveness by improving the logistics service quality, a 3PL company is required to run its business and provide a service in an efficient way. This research aims to propose strategy in increasing the logistics service quality and mitigating the risks in PT. Tiga Permata Logistik and PT. Tiga Permata Ekspres. This research applies House of Risk (HOR) in evaluating the risks or problems occurred in logistics service quality and generating the strategy required to improve the logistics service quality that will be provided by PT. Tiga Permata Logistik and PT. Tiga Permata Ekspres. The result of HOR I and the use of Pareto concepts shows that there are 12 critical risk agents and 3 critical indicator problems to be prioritized. Based on these critical risk agents and indicator problems, the improvement strategy is developed. The result of HOR II shows that there are 28 improvement strategies that can be implemented. These strategies used to increase Logistics Service Quality (LSQ) indicator and mitigate risks that potentially occur in this company

Sustainable supply chain management towards disruption and organizational ambidexterity:A data driven analysis

Balancing sustainability and disruption of supply chains requires organizational ambidexterity. Sustainable supply chains prioritize efficiency and economies of scale and may not have sufficient redundancy to withstand disruptive events. There is a developing body of literature that attempts to reconcile these two aspects. This study gives a data-driven literature review of sustainable supply chain management trends toward ambidexterity and disruption. The critical review reveals temporal trends and geographic distribution of literature. A hybrid of data-driven analysis approach based on content and bibliometric analyses, fuzzy Delphi method, entropy weight method, and fuzzy decision-making trial and evaluation laboratory is used on 273 keywords and 22 indicators obtained based on the experts’ evaluation. The most important indicators are identified as supply chain agility, supply chain coordination, supply chain finance, supply chain flexibility, supply chain resilience, and sustainability. The regions show different tendencies compared with others. Asia and Oceania, Latin America and the Caribbean, and Africa are the regions needs improvement, while Europe and North America show distinct apprehensions on supply chain network design. The main contribution of this review is the identification of the knowledge frontier, which then leads to a discussion of prospects for future studies and practical industry implementation

Proactive management of uncertainty to improve scheduling robustness in proces industries

Dinamisme, capacitat de resposta i flexibilitat són característiques essencials en el desenvolupament de la societat actual. Les noves tendències de globalització i els avenços en tecnologies de la informació i comunicació fan que s'evolucioni en un entorn altament dinàmic i incert. La incertesa present en tot procés esdevé un factor crític a l'hora de prendre decisions, així com un repte altament reconegut en l'àrea d'Enginyeria de Sistemes de Procés (PSE). En el context de programació de les operacions, els models de suport a la decisió proposats fins ara, així com també software comercial de planificació i programació d'operacions avançada, es basen generalment en dades estimades, assumint implícitament que el programa d'operacions s'executarà sense desviacions. La reacció davant els efectes de la incertesa en temps d'execució és una pràctica habitual, però no sempre resulta efectiva o factible. L'alternativa és considerar la incertesa de forma proactiva, és a dir, en el moment de prendre decisions, explotant el coneixement disponible en el propi sistema de modelització.Davant aquesta situació es plantegen les següents preguntes: què s'entén per incertesa? Com es pot considerar la incertesa en el problema de programació d'operacions? Què s'entén per robustesa i flexibilitat d'un programa d'operacions? Com es pot millorar aquesta robustesa? Quins beneficis comporta? Aquesta tesi respon a aquestes preguntes en el marc d'anàlisis operacionals en l'àrea de PSE. La incertesa es considera no de la forma reactiva tradicional, sinó amb el desenvolupament de sistemes proactius de suport a la decisió amb l'objectiu d'identificar programes d'operació robustos que serveixin com a referència pel nivell inferior de control de planta, així com també per altres centres en un entorn de cadenes de subministrament. Aquest treball de recerca estableix les bases per formalitzar el concepte de robustesa d'un programa d'operacions de forma sistemàtica. Segons aquest formalisme, els temps d'operació i les ruptures d'equip són considerats inicialment com a principals fonts d'incertesa presents a nivell de programació de la producció. El problema es modelitza mitjançant programació estocàstica, desenvolupant-se finalment un entorn d'optimització basat en simulació que captura les múltiples fonts d'incertesa, així com també estratègies de programació d'operacions reactiva, de forma proactiva. La metodologia desenvolupada en el context de programació de la producció s'estén posteriorment per incloure les operacions de transport en sistemes de múltiples entitats i incertesa en els temps de distribució. Amb aquesta perspectiva més àmplia del nivell d'operació s'estudia la coordinació de les activitats de producció i transport, fins ara centrada en nivells estratègic o tàctic. L'estudi final considera l'efecte de la incertesa en la demanda en les decisions de programació de la producció a curt termini. El problema s'analitza des del punt de vista de gestió del risc, i s'avaluen diferents mesures per controlar l'eficiència del sistema en un entorn incert.En general, la tesi posa de manifest els avantatges en reconèixer i modelitzar la incertesa, amb la identificació de programes d'operació robustos capaços d'adaptar-se a un ampli rang de situacions possibles, enlloc de programes d'operació òptims per un escenari hipotètic. La metodologia proposada a nivell d'operació es pot considerar com un pas inicial per estendre's a nivells de decisió estratègics i tàctics. Alhora, la visió proactiva del problema permet reduir el buit existent entre la teoria i la pràctica industrial, i resulta en un major coneixement del procés, visibilitat per planificar activitats futures, així com també millora l'efectivitat de les tècniques reactives i de tot el sistema en general, característiques altament desitjables per mantenir-se actiu davant la globalitat, competitivitat i dinàmica que envolten un procés.Dynamism, responsiveness, and flexibility are essential features in the development of the current society. Globalization trends and fast advances in communication and information technologies make all evolve in a highly dynamic and uncertain environment. The uncertainty involved in a process system becomes a critical problem in decision making, as well as a recognized challenge in the area of Process Systems Engineering (PSE). In the context of scheduling, decision-support models developed up to this point, as well as commercial advanced planning and scheduling systems, rely generally on estimated input information, implicitly assuming that a schedule will be executed without deviations. The reaction to the effects of the uncertainty at execution time becomes a common practice, but it is not always effective or even possible. The alternative is to address the uncertainty proactively, i.e., at the time of reasoning, exploiting the available knowledge in the modeling procedure itself. In view of this situation, the following questions arise: what do we understand for uncertainty? How can uncertainty be considered within scheduling modeling systems? What is understood for schedule robustness and flexibility? How can schedule robustness be improved? What are the benefits? This thesis answers these questions in the context of operational analysis in PSE. Uncertainty is managed not from the traditional reactive viewpoint, but with the development of proactive decision-support systems aimed at identifying robust schedules that serve as a useful guidance for the lower control level, as well as for dependent entities in a supply chain environment. A basis to formalize the concept of schedule robustness is established. Based on this formalism, variable operation times and equipment breakdowns are first considered as the main uncertainties in short-term production scheduling. The problem is initially modeled using stochastic programming, and a simulation-based stochastic optimization framework is finally developed, which captures the multiple sources of uncertainty, as well as rescheduling strategies, proactively. The procedure-oriented system developed in the context of production scheduling is next extended to involve transport scheduling in multi-site systems with uncertain travel times. With this broader operational perspective, the coordination of production and transport activities, considered so far mainly in strategic and tactical analysis, is assessed. The final research point focuses on the effect of demands uncertainty in short-term scheduling decisions. The problem is analyzed from a risk management viewpoint, and alternative measures are assessed and compared to control the performance of the system in the uncertain environment.Overall, this research work reveals the advantages of recognizing and modeling uncertainty, with the identification of more robust schedules able to adapt to a wide range of possible situations, rather than optimal schedules for a hypothetical scenario. The management of uncertainty proposed from an operational perspective can be considered as a first step towards its extension to tactical and strategic levels of decision. The proactive perspective of the problem results in a more realistic view of the process system, and it is a promising way to reduce the gap between theory and industrial practices. Besides, it provides valuable insight on the process, visibility for future activities, as well as it improves the efficiency of reactive techniques and of the overall system, all highly desirable features to remain alive in the global, competitive, and dynamic process environment

A Structured Approach to Analyse Logistics Risks in the Blood Transfusion Process

Blood transfusion is a critical healthcare process due to the nature of the products handled and the complexity driven by the strong interdependence among the sub-processes involved. Most of the errors causing adverse events originate during the blood logistics activities. Several literature contributions apply risk management to the transfusion process but often in a fragmented and reactive way. Moreover, few of them focus on logistics risks and assess the effectiveness of risk responses through operational key performance indicators (KPIs). The present paper applies a comprehensive and structured approach to proactively identify and analyse logistics risks as well as define responses to improve blood bag traceability, focusing on hospital wards. The implementation of such actions is monitored by specific KPIs whose measurement enables an improved communication flow among actors allowing to uncover residual risks. Future research will extend the application to further blood transfusion settings and supply chain echelons. The outcomes of this work might assist practitioners in improving policy making about blood supply chains. As a matter of fact, they allow a better understanding of the associated material and informational flows and the related risks, which supports setting effective strategies to either prevent adverse events or mitigate their effects

Effectiveness of interventions to identify and manage patients with familial cancer risk in primary care: a systematic review

This systematic review evaluated the effectiveness of strategies to identify and manage patients with familial risk of breast, ovarian, colorectal and prostate cancer in primary careto improve clinical outcomes. MEDLINE, EMBASE, CINAHL and Cochrane library were searched from January 1980 to October 2017. We included randomised controlled trials (RCT) and non-randomised studies of interventions (NRSI). Primary outcomes were cancer incidence, cancer related clinical outcomes or identification of cancer predisposition; secondary outcomes were appropriateness of referral, uptake of preventive strategies, cognitive and psychological effect. From 11842 abstracts, 111 full texts were reviewed and three eligible studies (nine articles) identified. Two were cluster RCTs and one NRSI; all used risk assessment software. No studies identified our primary outcomes, with no consistent outcome across the three studies. In one RCT, intervention improved the proportion of genetic referrals meeting referral guidelines for breast cancer (OR 4.5, 95% CI 1.6 to 13.1). In the other RCT, there was no difference in screening adherence between the intervention and control group. However, there was borderline increased risk perception (OR 1.89, 95% CI 0.99 to 3.59) in the subgroup that under-estimated their colon cancer risk. In the NRSI, there was no change in psychological distress inpatients at increased familial breast cancer risk, but population risk patients had reduced anxiety after intervention (state anxiety mean change –3,95% CI -5 to -2). Future studies should have better defined comparator groups, longer follow up, and assess outcomes using validated tools