WATERFALL METHOD OF WEB-BASED SYSTEM TO DEVELOP WAREHOUSE PACKING EFFECTIVELY

This study aims to develop an efficient Warehouse Packing System for PT Luna Technology Group in order to improve operational efficiency and minimize packing errors in logistics processes. The research adopts the Waterfall Method, employing a systematic approach that encompasses requirements analysis, system design, implementation, and testing. Data was collected through qualitative observational methods, including interviews and direct observations of the existing packing processes. The findings demonstrate that the implementation of a web-based packing system significantly reduces packing times, mitigates errors in item selection, and lowers operational costs compared to the previous manual methods. The research concludes that embracing a structured software development methodology not only enhances the packing process, but also positions PT Luna Technology Group as a competitive player in the logistics industry, underscoring the need for continuous technological advancements in warehouse management

Facility Location Planning in Relief Logistics: Decision Support for German Authorities

Disasters have devastating impacts on societies, affecting millions of people and businesses each year. The delivery of essential goods to beneficiaries in the aftermath of a disaster is one of the main objectives of relief logistics. In this context, selecting suitable locations for three different types of essential facilities is central: warehouses, distribution centers, and points of distribution. The present dissertation aims to improve relief logistics by advancing the location selection process and its core components. Five studies published as companion articles address substantial aspects of relief logistics. Despite the case studies\u27 geographical focus on Germany, valuable insights for relief logistics are derived that could also be applied to other countries. Study A addresses the importance of public-private collaboration in disasters and highlights the significance of considering differences in resources, capabilities, and strategies when using logistical models. Moreover, power differences, information sharing, and partner selection also play an important role. Study B elaborates on the challenges to identify candidate locations for warehouses, which are jointly used by public and private actors, and suggests a methodology to approach the collaborative warehouse selection process. Study C investigates the distribution center selection process and highlights that including decision-makers\u27 preferences in the objective function of location selection models helps to raise awareness of the implications of location decisions and increases transparency for decision-makers and the general population. Study D analyzes the urban water supply in disasters using a combination of emergency wells and mobile water treatment systems. Selected locations of mobile systems change significantly if vulnerable parts of the population are prioritized. Study E highlights the importance of accurate information in disasters and introduces a framework that allows determining the value of accurate information and the planning error due to inaccurate information. In addition to the detailed results of the case studies, four general recommendations for authorities are derived: First, it is essential to collect information before the start of the disaster. Second, training exercises or role-playing simulations with companies will help to ensure that planned collaboration processes can be implemented in practice. Third, targeted adjustments to the German disaster management system can strengthen the country\u27s resilience. Fourth, initiating public debates on strategies to prioritize parts of the population might increase the acceptance of the related decision and the stockpiling of goods for the people who know in advance that they will likely not receive support. The present dissertation provides valuable insights into disaster relief. Therefore, it offers the potential to significantly improve the distribution of goods in the aftermath of future disasters and increase disaster resilience

Tecnología para Tiendas Inteligentes

Trabajo de Fin de Grado en Doble Grado en Ingeniería Informática y Matemáticas, Facultad de Informática UCM, Departamento de Ingeniería del Software e Inteligencia Artificial, Curso 2020/2021Smart stores technologies exemplify how Artificial Intelligence and Internet of Things can effectively join forces to shape the future of retailing. With an increasing number of companies proposing and implementing their own smart store concepts, such as Amazon Go or Tao Cafe, a new field is clearly emerging. Since the technologies used to build their infrastructure offer significant competitive advantages, companies are not publicly sharing their own designs. For this reason, this work presents a new smart store model named Mercury, which aims to take the edge off of the lack of public and accessible information and research documents in this field. We do not only introduce a comprehensive smart store model, but also work-through a feasible detailed implementation so that anyone can build their own system upon it.Las tecnologías utilizadas en las tiendas inteligentes ejemplifican cómo la Inteligencia Artificial y el Internet de las Cosas pueden unir, de manera efectiva, fuerzas para transformar el futuro de la venta al por menor. Con un creciente número de empresas proponiendo e implementando sus propios conceptos de tiendas inteligentes, como Amazon Go o Tao Cafe, un nuevo campo está claramente emergiendo. Debido a que las tecnologías utilizadas para construir sus infraestructuras ofrecen una importante ventaja competitiva, las empresas no están compartiendo públicamente sus diseños. Por esta razón, este trabajo presenta un nuevo modelo de tienda inteligente llamado Mercury, que tiene como objetivo mitigar la falta de información pública y accesible en este campo. No solo introduciremos un modelo general y completo de tienda inteligente, sino que también proponemos una implementación detallada y concreta para que cualquier persona pueda construir su propia tienda inteligente siguiendo nuestro modelo.Depto. de Ingeniería de Software e Inteligencia Artificial (ISIA)Fac. de InformáticaTRUEunpu

Value Stream Mapping with Microsoft Dynamics AX

Microsoft Dynamics AX (AX) is an Enterprise Resource Planning (ERP) system, and like ERP systems in general, it supports the lean production philosophy only to a limited extent. One way to provide a better support for lean production would be a feature for value stream mapping with AX as data source. The purpose of this study was to examine if plant level current state value stream maps could be created with an existing software using AX as data source. The relevance of such maps in order to gain a realistic representation of the value stream has also been evaluated. In order to fulfil the purpose, a comprehensive literature study has been conducted. From established theories, the information needed for mapping of a value stream has been identified. Next it has been investigated to what extent this information is available in AX, and how it can be visualized. Finally it is investigated how relevant this visualization is for realistically describing the actual value stream. A number of additional value stream mapping tools are also examined, in relation to the existing data in AX. It is concluded that plant level current state value stream maps can be created with data from AX and that this method of producing value stream maps has some advantages in relation to the conventional method: A time saving potential, clearness, and a single source of data. Disadvantages are also identified, including: Risk for lack of specific data, approximations of data, reliance on user input and frequent updating. It is also concluded that this method of value stream mapping is limited in relation to the lean principles, mainly due to two facts: Strategic product families can not be identified, and AX does not support the way production is controlled in a lean production environment. Therefore further research is suggested, before a feature for value stream mapping is implemented

Through What Mechanisms Does Business Analytics Contribute To Business Value?

This paper synthesizes from the literature a model of factors affecting organizational benefits from business analytics, then reports a preliminary test of that model. The model consists of two parts: a process model and a variance model. The process model depicts the analyse-insight-decision-action process through which an organization’s business-analytic capabilities (high-quality data, integrated BA platform, and analytic people) create business value. The variance model proposes that the five factors in Davenport et al.’s (2010) DELTA model of BA success factors, plus three from Seddon et al.’s (2010) model of factors affecting organizational benefits from enterprise systems, assist a firm to embed evidence-based decision making in the organization, and so contribute to business value. A preliminary test of the model was conducted using data from 40 customer-success stories from IBM, SAP and Teradata websites. Our conclusion was that the model is likely to be a useful basis for future research

Correlated storage assignment approach in warehouses: A systematic literature review

Purpose: Correlation-based storage assignment approach has been intensively explored during the last three decades to improve the order picking efficiency. The purpose of this study is to present a comprehensive assessment of the literature about the state-of-the-art techniques used to solve correlated storage location assignment problems (CSLAP). Design/methodology/approach: A systematic literature review has been carried out based on content analysis to identify, select, analyze, and critically summarize all the studies available on CSLAP. This study begins with the selection of relevant keywords, and narrowing down the selected papers based on various criteria. Findings: Most correlated storage assignment problems are expressed as NP-hard integer programming models. The studies have revealed that CSLAP is evaluated with many approaches. The solution methods can be mainly categorized into heuristic approach, meta-heuristic approach, and data mining approach. With the advancement of computing power, researchers have taken up the challenge of solving more complex storage assignment problems. Furthermore, applications of the models developed are being tested on actual industry data to comprehend the efficiency of the models. Practical implications: The content of this article can be used as a guide to help practitioners and researchers to become adequately knowledgeable on CSLAP for their future work. Originality/value: Since there has been no recent state-of-the-art evaluation of CSLAP, this paper fills that need by systematizing and unifying recent work and identifying future research scopes

Wal-Mart Stores, Inc. Strategic Corporate Research Report

[Excerpt] Wal-Mart Stores, Inc. (hereinafter Wal-Mart) is the second-largest company in the world. It has more annual revenue than the GDP of Switzerland. It sells more DVDs, magazines, books, CDs, dog food, diapers, bicycles, toys, toothpaste, jewelry, and groceries than any other retailer does worldwide. It is the largest retailer in the United States, Mexico, and Canada, the second-largest in the United Kingdom, and the third largest in Brazil, With its partners, it is the largest retailer in Central America. Wal-Mart is also the largest private employer in the United States, Mexico, and Canada, and it has 1.8 million employees around the globe. Wal-Mart is so huge that it effectively sets the terms for large swaths of the global economy, from retail wages to apparel prices to transoceanic shipping rates to the location of toy factories. Indeed, if there is one single aspect to understand about the company, it is the fact that Wal-Mart is transforming the relations of production in virtually every product category it sells, through its relationships with suppliers. But its influence goes far beyond the economy. It sets social policy by refusing to sell certain types of birth control. Its construction of supercenters molds the landscape, shapes traffic patterns, and alters the local commercial mix. The retail goliath shapes culture by selling the music of patriotic country singer Garth Brooks but not the critical (and hilarious) The Daily Show with Jon Stewart Presents America (the Book): A Citizen’s Guide to Democracy Inaction. It influences politics by donating millions to conservative politicians and think tanks. Wal-Mart is, in short, one of the most powerful entities in the world. Not surprisingly, Wal-Mart has developed a long list of critics, including unions, human rights organizations, religious groups, environmental activists, community organizations, small business groups, academics, children’s rights groups, and even institutional investors. These groups have exposed the company’s illegal union-busting tactics, its many violations of overtime laws, its abuse of child labor, its egregious healthcare policies, its super-exploitation of immigrant workers, its rampant gender discrimination, the horrific labor conditions at its suppliers’ factories, and its unlawful environmental degradation. They have also chronicled the deleterious effect Wal-Mart has on the public coffers and the quality of community life. New Wal-Mart stores and distribution centers often swallow up government subsidies and tax breaks, take public land, create more congestion, reduce overall wages, destroy retail variety, and increase public outlays for healthcare. To its critics, Wal-Mart represents the worst aspects of 21st-eentury capitalism. Wal-Mart usually counters any criticism with two words: low prices. It is a powerful mantra in a consumerist world. The company does make more products affordable to more people, and that is nothing to sneeze at when wages are stagnant, jobs insecure, pensions disappearing, and health coverage shrinking. With low prices, Wal-Mart helps working men and women get more from their meager paychecks, more necessities like bread, and more luxuries, like roses, too. It is a brilliant and incontrovertible argument, and Wal-Mart’s most ardent defenders take it even farther. They say its obsession with low prices makes the entire economy more efficient and more productive. Suppliers and competitors have to produce more and better products with the same resources, and that redounds to everyone. In the micro, it means falling prices and rising product quality. In the macro, it means economic growth, more jobs, and higher tax revenues. To its defenders, Wal-Mart represents the best aspects of 21st-century capitalism. Despite their radical opposition, critics and defenders of the world’s largest corporation agree on one thing: Wal-Mart represents 21st-century capitalism. It symbolizes a system of increasing market penetration and decreasing social regulation, where more and more aspects of life around the world are subject to economic competition. Wal-Mart’s success rests upon the ongoing destruction of social power in favor of corporate power. It takes advantage of the conditions of the neo-liberal world, from the availability of instant and inexpensive global communication to the continuing collapse of agricultural employment around the world to the rapid diffusion of technological innovation to the oversupply of subjugated migrant labor in nearly every country to the continued existence of undemocratic and corporate-dominated governments. For some, this is as it should be, all part of capitalism’s natural and ultimately benign development. For the rest of us, Wal-Mart is at the heart of what is wrong with the world

Practices that organizations employ to enhance business intelligence agility

In today's rapidly changing business environment, organizations strive to be agile in order to accommodate changes and seize opportunities. Since organizations use information system as a tool to serve their needs, it is important for these systems also to be agile. One prominent type of such systems is business intelligence, which provides organizations with information to gain and retain competitive advantage. This thesis focuses on business intelligence agility, which is widely discussed in practice however not extensively covered in information systems literature. Therefore, this thesis seeks to identify the practices employed by organizations to enhance business intelligence agility. To find the answer to the research question this thesis first compiles a theoretical framework on business intelligence, information systems agility in general and business intelligence agility in specific using academic literature and market white papers. This compiled framework is comprised of four enabling factors 1) sensing business changes, 2) development approach, 3) IT governance, and 4) technical factors. This thesis conducts a qualitative research based on semi-structured interviews with business intelligence experts. Based on analysis of the empirical data this thesis identified a set of practices organized in terms of the enabling factors. The practices in sensing business changes are enabling business staff to sense changes and incorporating business staff feedback into data requirements. Regarding development approach, this thesis identifies the practices as applying an iterative development approach, building collaborative team of skilled members, enabling a centric role of business staff, reducing use of approval documents and learning from each project. In IT governance, applying a centralized or decentralized development were the two practices. Regarding practices in technical factors, this thesis identifies integrating data through either building an enterprise-wide data warehouse or applying an appropriate modeling approach while managing multiple data warehouses, using multiple front-end applications, and adopting cloud business intelligence. The findings of this thesis provide organizations with a pool of practices that can be used to enhance business intelligence agility

Comparative Analysis To Determine Predictive Model Accuracy : A dynamic currency exchange rate predictive model development using SAP HANA Predictive Analytic Library (PAL) algorithm

The present thesis describes the development and implementation of a dynamic currency exchange rate predictive model. The aim of the thesis was to measure and determine the accuracy of a dynamic currency exchange rate predictive model by analysing different historical data samples. The theoretical framework of the thesis focused on research into different disciplines related to predicted analytics and the different data mining algorithms. The study was carried out using quantitative data samples and SAP high performance analytic appliance predictive analysis library (PAL) Time series double exponential algorithm. The measurement was done by comparing the predicted or forecasted exchange rates against the actual exchange rates. Standard statistical methods were used to determine the accuracy of the predictive model. The results of the study showed that last three months data sample or most recent data gives better predictive results for short term forecasting while the full data sample or entire data set gives better result for longer term forecasting. Based on the study, it is recommended that fundamental analysis of currency exchange method which takes account of the driving forces behind currency exchange rates such as political and economic situation, the rise and fall of interest rates and other economic indicators should be incorporated along technical analysis which involves the use of historical data to get give better accuracy

A Secondary Packaging Solution Development Suitable for E-groceries through the Identification of Food Product and Logistic Requirements

Secondary packaging solutions presently used to package food goods in e-commerce supply chain are either taken from old supply chains, or sub-optimally developed in a non-holistic manner. Due to the increase use of the Internet in Europe to perform online food purchases, secondary packaging must be adapted to meet these new needs. Therefore, a secondary packaging solution for a Dutch e-grocer was devised through a case study and the identification of food product and logistic requirements for such a packaging. Identified requirements were found to be fulfilled by the use of packaging features. Food product requirements that have to be considered during the development of a secondary packaging for food in e-commerce benefit product quality assurance. These requirements are the control of temperature over time, the reduction of product damage and the separation of food product types. Logistics requirements that must be considered for secondary packaging solutions for food in e-commerce relate to last mile logistics. This entails fulfilment, transportation, delivery and return-logistics. Applying these results during the secondary packaging solution development for the case study resulted in the finding of suitable value-adding packaging features to address the above mentioned requirements. Separators in the secondary packaging facilitate eased fulfilment, increase the stackability of packaging, as it provides a larger surface area on which more crates can be stacked. Increased stackability influences volume efficiency and reduces the need for extra packaging levels. Time temperature indicators increase quality assurance and a deposit-refund system can induce incentive for customers to return the used packaging levels