Design System Fuel Inventory Control In Gas Stations With The Concept Of Min-Max Stock Level And Time Phased Order Point Case Study Gas Stations 44.501.01

The concept of supply chain inventory requirement has been widely used by companies to improve meeting the needs of its customers. Lost sales due to inventory shortage is an important thing to be avoided by the company. This research aims to build a inventory control system supplies fuel to the method of Distribution Requirements Planning (DRP) web-based on gas stations in the area of Semarang. The method used for planning is the ordering of distribution requirements planning with the stage of determining the net requirements (netting), selection Lot (lotting), the timing of orders (offsetting) and the determination of gross requirements for next level (exploision). The Time Phased Order Point and min-max stock level Consept used for optimalitation needs Planning. Model Design of the system is using waterfall model which consists of system analysis, system design, system implementation and testing programs. The research design of this system is the ordering of the supply system can be used to support and improve inventory control at retail outlets. The results of testing the system states that the system developed to support inventory control, increased security at gas stations supply needs to be better and minimize losses orders. Keywords: Inventory Control; Needs Planning; Time Phased Order Point; Distribution Requirement Planning; Design system; Waterfall mode

Intelligent Products: Shifting the Production Control Logic in Construction (With Lean and BIM)

Production management and control in construction has not been addressed/updated ever since the introduction of Critical Path Method and the Last Planner® system. The predominant outside-in control logic and a fragmented and deep supply chain in construction significantly affect the efficiency over a lifecycle. In a construction project, a large number of organisations interact with the product throughout the process, requiring a significant amount of information handling and synchronisation between these organisations. However, due to the deep supply chains and problems with lack of information integration, the information flow down across the lifecycle poses a significant challenge. This research proposes a product centric system, where the control logic of the production process is embedded within the individual components from the design phase. The solution is enabled by a number of technologies and tools such as Building Information Modelling, Internet of Things, Messaging Systems and within the conceptual process framework of Lean Construction. The vision encompasses the lifecycle of projects from design to construction and maintenance, where the products can interact with the environment and its actors through various stages supporting a variety of actions. The vision and the tools and technologies required to support it are described in this pape

The relationship between the Last Planner® System and collaborative planning practice in UK construction

Purpose – The purpose of this study is to identify how the newly emerging UK practice of "Collaborative Planning" (CP) for construction project delivery aligns with the advocated principles of the Last Planner System (LPS) of production planning and control. Design/methodology/approach – A mixed, qualitative, exploratory approach was adopted for the study. This entailed qualitative data through three techniques namely: semi-structured interviews, documents analysis, and structured observation. Thirty in-depth-interviews were conducted over a 12 month period with lean construction consultants, clients, main contractors, and subcontractors drawn from the building, highways and infrastructure and rail sector. Fifteen projects were visited where practices were observed. Findings – The study reveals that the current practice of CP in the UK partially aligns with the LPS principles. Where practitioners have heard of the LPS they believe it to be the same practice as CP. Limitation: This study is limited to 30 interviews, observation of 15 projects and document analysis. The aim of the study is not to generalise the findings, however, since the study examined top construction companies and practitioners in the UK and the findings were consistent across the sample, some conclusions could be made. The study is also limited to examining the construction phase only, future studies should incorporate the design phase. Practical Implication - A clear identification of the elements of current practice compared to the components of the LPS provides a contribution to the future practice of project production planning and management in the construction industry. Social implication – The study highlights a continuing resistance to collaboration within the industry. This resistance is subtly embedded within implemented practices even though they are based on collaborative working for their success. Originality and Value – This is among the first studies in the UK that comprehensively examines and reports the application of Last Planner System/Collaborative Planning practice in construction across the major construction sectors. Future studies could build on the findings from this work to develop an approach/methodology to improve the current practice

Models and Algorithms for the Optimisation of Replenishment, Production and Distribution Plans in Industrial Enterprises

Tesis por compendio[ES] La optimización en las empresas manufactureras es especialmente importante, debido a las grandes inversiones que realizan, ya que a veces estas inversiones no obtienen el rendimiento esperado porque los márgenes de beneficio de los productos son muy ajustados. Por ello, las empresas tratan de maximizar el uso de los recursos productivos y financieros minimizando el tiempo perdido y, al mismo tiempo, mejorando los flujos de los procesos y satisfaciendo las necesidades del mercado. El proceso de planificación es una actividad crítica para las empresas. Esta tarea implica grandes retos debido a los cambios del mercado, las alteraciones en los procesos de producción dentro de la empresa y en la cadena de suministro, y los cambios en la legislación, entre otros. La planificación del aprovisionamiento, la producción y la distribución desempeña un papel fundamental en el rendimiento de las empresas manufactureras, ya que una planificación ineficaz de los proveedores, los procesos de producción y los sistemas de distribución contribuye a aumentar los costes de los productos, a alargar los plazos de entrega y a reducir los beneficios. La planificación eficaz es un proceso complejo que abarca una amplia gama de actividades para garantizar que los equipos, los materiales y los recursos humanos estén disponibles en el momento y el lugar adecuados. Motivados por la complejidad de la planificación en las empresas manufactureras, esta tesis estudia y desarrolla herramientas cuantitativas para ayudar a los planificadores en los procesos de la planificación del aprovisionamiento, producción y distribución. Desde esta perspectiva, se proponen modelos realistas y métodos eficientes para apoyar la toma de decisiones en las empresas industriales, principalmente en las pequeñas y medianas empresas (PYMES). Las aportaciones de esta tesis suponen un avance científico basado en una exhaustiva revisión bibliográfica sobre la planificación del aprovisionamiento, la producción y la distribución que ayuda a comprender los principales modelos y algoritmos utilizados para resolver estos planes, y pone en relieve las tendencias y las futuras direcciones de investigación. También proporciona un marco holístico para caracterizar los modelos y algoritmos centrándose en la planificación de la producción, la programación y la secuenciación. Esta tesis también propone una herramienta de apoyo a la decisión para seleccionar un algoritmo o método de solución para resolver problemas concretos de la planificación del aprovisionamiento, producción y distribución en función de su complejidad, lo que permite a los planificadores no duplicar esfuerzos de modelización o programación de técnicas de solución. Por último, se desarrollan nuevos modelos matemáticos y enfoques de solución de última generación, como los algoritmos matheurísticos, que combinan la programación matemática y las técnicas metaheurísticas. Los nuevos modelos y algoritmos comprenden mejoras en términos de rendimiento computacional, e incluyen características realistas de los problemas del mundo real a los que se enfrentan las empresas de fabricación. Los modelos matemáticos han sido validados con un caso de una importante empresa del sector de la automoción en España, lo que ha permitido evaluar la relevancia práctica de estos novedosos modelos utilizando instancias de gran tamaño, similares a las existentes en la empresa objeto de estudio. Además, los algoritmos matheurísticos han sido probados utilizando herramientas libres y de código abierto. Esto también contribuye a la práctica de la investigación operativa, y proporciona una visión de cómo desplegar estos métodos de solución y el tiempo de cálculo y rendimiento de la brecha que se puede obtener mediante el uso de software libre o de código abierto.[CA] L'optimització a les empreses manufactureres és especialment important, a causa de les grans inversions que realitzen, ja que de vegades aquestes inversions no obtenen el rendiment esperat perquè els marges de benefici dels productes són molt ajustats. Per això, les empreses intenten maximitzar l'ús dels recursos productius i financers minimitzant el temps perdut i, alhora, millorant els fluxos dels processos i satisfent les necessitats del mercat. El procés de planificació és una activitat crítica per a les empreses. Aquesta tasca implica grans reptes a causa dels canvis del mercat, les alteracions en els processos de producció dins de l'empresa i la cadena de subministrament, i els canvis en la legislació, entre altres. La planificació de l'aprovisionament, la producció i la distribució té un paper fonamental en el rendiment de les empreses manufactureres, ja que una planificació ineficaç dels proveïdors, els processos de producció i els sistemes de distribució contribueix a augmentar els costos dels productes, allargar els terminis de lliurament i reduir els beneficis. La planificació eficaç és un procés complex que abasta una àmplia gamma d'activitats per garantir que els equips, els materials i els recursos humans estiguen disponibles al moment i al lloc adequats. Motivats per la complexitat de la planificació a les empreses manufactureres, aquesta tesi estudia i desenvolupa eines quantitatives per ajudar als planificadors en els processos de la planificació de l'aprovisionament, producció i distribució. Des d'aquesta perspectiva, es proposen models realistes i mètodes eficients per donar suport a la presa de decisions a les empreses industrials, principalment a les petites i mitjanes empreses (PIMES). Les aportacions d'aquesta tesi suposen un avenç científic basat en una exhaustiva revisió bibliogràfica sobre la planificació de l'aprovisionament, la producció i la distribució que ajuda a comprendre els principals models i algorismes utilitzats per resoldre aquests plans, i posa de relleu les tendències i les futures direccions de recerca. També proporciona un marc holístic per caracteritzar els models i algorismes centrant-se en la planificació de la producció, la programació i la seqüenciació. Aquesta tesi també proposa una eina de suport a la decisió per seleccionar un algorisme o mètode de solució per resoldre problemes concrets de la planificació de l'aprovisionament, producció i distribució en funció de la seua complexitat, cosa que permet als planificadors no duplicar esforços de modelització o programació de tècniques de solució. Finalment, es desenvolupen nous models matemàtics i enfocaments de solució d'última generació, com ara els algoritmes matheurístics, que combinen la programació matemàtica i les tècniques metaheurístiques. Els nous models i algoritmes comprenen millores en termes de rendiment computacional, i inclouen característiques realistes dels problemes del món real a què s'enfronten les empreses de fabricació. Els models matemàtics han estat validats amb un cas d'una important empresa del sector de l'automoció a Espanya, cosa que ha permés avaluar la rellevància pràctica d'aquests nous models utilitzant instàncies grans, similars a les existents a l'empresa objecte d'estudi. A més, els algorismes matheurístics han estat provats utilitzant eines lliures i de codi obert. Això també contribueix a la pràctica de la investigació operativa, i proporciona una visió de com desplegar aquests mètodes de solució i el temps de càlcul i rendiment de la bretxa que es pot obtindre mitjançant l'ús de programari lliure o de codi obert.[EN] Optimisation in manufacturing companies is especially important, due to the large investments they make, as sometimes these investments do not obtain the expected return because the profit margins of products are very tight. Therefore, companies seek to maximise the use of productive and financial resources by minimising lost time and, at the same time, improving process flows while meeting market needs. The planning process is a critical activity for companies. This task involves great challenges due to market changes, alterations in production processes within the company and in the supply chain, and changes in legislation, among others. Planning of replenishment, production and distribution plays a critical role in the performance of manufacturing companies because ineffective planning of suppliers, production processes and distribution systems contributes to higher product costs, longer lead times and less profits. Effective planning is a complex process that encompasses a wide range of activities to ensure that equipment, materials and human resources are available in the right time and the right place. Motivated by the complexity of planning in manufacturing companies, this thesis studies and develops quantitative tools to help planners in the replenishment, production and delivery planning processes. From this perspective, realistic models and efficient methods are proposed to support decision making in industrial companies, mainly in small- and medium-sized enterprises (SMEs). The contributions of this thesis represent a scientific breakthrough based on a comprehensive literature review about replenishment, production and distribution planning that helps to understand the main models and algorithms used to solve these plans, and highlights trends and future research directions. It also provides a holistic framework to characterise models and algorithms by focusing on production planning, scheduling and sequencing. This thesis also proposes a decision support tool for selecting an algorithm or solution method to solve concrete replenishment, production and distribution planning problems according to their complexity, which allows planners to not duplicate efforts modelling or programming solution techniques. Finally, new state-of-the-art mathematical models and solution approaches are developed, such as matheuristic algorithms, which combine mathematical programming and metaheuristic techniques. The new models and algorithms comprise improvements in computational performance terms, and include realistic features of real-world problems faced by manufacturing companies. The mathematical models have been validated with a case of an important company in the automotive sector in Spain, which allowed to evaluate the practical relevance of these novel models using large instances, similarly to those existing in the company under study. In addition, the matheuristic algorithms have been tested using free and open-source tools. This also helps to contribute to the practice of operations research, and provides insight into how to deploy these solution methods and the computational time and gap performance that can be obtained by using free or open-source software.This work would not have been possible without the following funding sources: Conselleria de Educación, Investigación, Cultura y Deporte, Generalitat Valenciana for hiring predoctoral research staff with Grant (ACIF/2018/170) and the European Social Fund with the Grant Operational Programme of FSE 2014-2020. Conselleria de Educación, Investigación, Cultura y Deporte, Generalitat Valenciana for predoctoral contract students to stay in research centers outside the research centers outside the Valencian Community (BEFPI/2021/040) and the European Social Fund.Guzmán Ortiz, BE. (2022). Models and Algorithms for the Optimisation of Replenishment, Production and Distribution Plans in Industrial Enterprises [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/187461Compendi

A Layered Software Architecture for the Management of a Manufacturing Company

In this paper we describe a layered software architecture in the management of a manufactur-ing company that intensively uses computer technology. Application tools, new and legacy, after the updating, operate in a context of an open web oriented architecture. The software architecture enables the integration and interoperability among all tools that support business processes. Manufacturing Executive System and Text Mining tools are excellent interfaces, the former both for internal production and management processes and the latter for external processes coming from the market. In this way, it is possible to implement, a computer integrated factory, flexible and agile, that immediately responds to customer requirements.ICT, Service Oriented Architecture, Web Services, Computer-Integrated Factory, Application Software

Research on Cloud Enterprise Resource Integration and Scheduling Technology Based on Mixed Set Programming

With the development of Industry 4.0 and intelligent manufacturing, aiming at the incompatibility of heterogeneous manufacturing resource interfaces and the low efficiency of collaborative scheduling of manufacturing resources among enterprises，we proposed the resource integration and scheduling strategy among enterprises based on Mixed Set Programming [1]. By using the metadata and ontology modeling methods, we were able to realize a standardized model description of manufacturing resources. At last, an enterprise application case was discussed to verify the resources integration and scheduling strategy based on Mixed Set Programming is effective to optimize and improve the efficiency of the collaborative scheduling of resources among enterprises. The resources integration and scheduling strategy based on Mixed Set Programming could be applied to promote the optimal allocation of manufacturing resources

Non-linear time-cost trade-off models of activity crashing: Application to construction scheduling and project compression with fast-tracking

When shortening a project’s duration, activity crashing, fast-tracking and substitution are the three most commonly employed compression techniques. Crashing generally involves allocating extra resources to an activity with the intention of reducing its duration. To date, the activity time-cost relationship has for the most part been assumed to be linear, however, a few studies have suggested that this is not necessarily the case in practice. This paper proposes two non-linear theoretical models which assume either collaborative or non-collaborative resources. These models closely depict the two most common situations occurring during construction projects. The advantages of these models are that they allow for both discrete and continuous, as well as deterministic and stochastic configurations. Additionally, the quantity of resources required for crashing the activity can be quantified. Comparisons between the models and another recent fast-tracking model from the literature are discussed, and a Genetic Algorithm is implemented for a fictitious application example involving both compression techniques

Non-linear time-cost trade-off models of activity crashing: Application to construction scheduling and project compression with fast-tracking

[EN] When shortening a project's duration, activity crashing, fast-tracking and substitution are the three most commonly employed compression techniques. Crashing generally involves allocating extra resources to an activity with the intention of reducing its duration. To date, the activity time-cost relationship has for the most part been assumed to be linear, however, a few studies have suggested that this is not necessarily the case in practice. This paper proposes two non-linear theoretical models which assume either collaborative or non-collaborative resources. These models closely depict the two most common situations occurring during construction projects. The advantages of these models are that they allow for both discrete and continuous, as well as deterministic and stochastic configurations. Additionally, the quantity of resources required for crashing the activity can be quantified. Comparisons between the models and another recent fast-tracking model from the literature are discussed, and a Genetic Algorithm is implemented for a fictitious application example involving both compression techniques.This research was supported by the CIOB Bowen Jenkins Legacy Research Fund (reference BLJ2016/BJL.01) and by NERC under the Environmental Risks to Infrastructure Innovation Programme (reference NE/R008876/1) at the University of Reading.Ballesteros-Pérez, P.; Elamrousy, KM.; González-Cruz, M. (2019). Non-linear time-cost trade-off models of activity crashing: Application to construction scheduling and project compression with fast-tracking. Automation in Construction. 97:229-240. https://doi.org/10.1016/j.autcon.2018.11.0012292409