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Vázquez, M. Velasco-Villa" "autores" => array:2 [ 0 => array:2 [ "nombre" => "J.A." "apellidos" => "Vázquez" ] 1 => array:2 [ "nombre" => "M." "apellidos" => "Velasco-Villa" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1665642313715451?idApp=UINPBA00004N" "url" => "/16656423/0000001100000003/v2_201505081636/S1665642313715451/v2_201505081636/en/main.assets" ] "itemAnterior" => array:18 [ "pii" => "S1665642313715438" "issn" => "16656423" "doi" => "10.1016/S1665-6423(13)71543-8" "estado" => "S300" "fechaPublicacion" => "2013-06-01" "aid" => "71543" "copyright" => "Universidad Nacional Autónoma de México" "documento" => "article" "licencia" => "http://creativecommons.org/licenses/by-nc-nd/4.0/" "subdocumento" => "fla" "cita" => "Journal of Applied Research and Technology. 2013;11:331-7" "abierto" => array:3 [ "ES" => true "ES2" => true "LATM" => true ] "gratuito" => true "lecturas" => array:2 [ "total" => 1329 "formatos" => array:3 [ "EPUB" => 39 "HTML" => 947 "PDF" => 343 ] ] "en" => array:11 [ "idiomaDefecto" => true "titulo" => "High-Speed Decoding of the Binary Golay Code" "tienePdf" => "en" "tieneTextoCompleto" => "en" "tieneResumen" => "en" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "331" "paginaFinal" => "337" ] ] "contieneResumen" => array:1 [ "en" => true ] "contieneTextoCompleto" => array:1 [ "en" => true ] "contienePdf" => array:1 [ "en" => true ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "f0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 721 "Ancho" => 819 "Tamanyo" => 146668 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0005" class="elsevierStyleSimplePara elsevierViewall">Decoding Time of Two Hard-Decision Decoders at SNR of 0~6 dB.</p>" ] ] ] "autores" => array:1 [ 0 => array:2 [ "autoresLista" => "H.P. Lee, C.H. Chang, S.I. Chu" "autores" => array:3 [ 0 => array:2 [ "nombre" => "H.P." "apellidos" => "Lee" ] 1 => array:2 [ "nombre" => "C.H." "apellidos" => "Chang" ] 2 => array:2 [ "nombre" => "S.I." "apellidos" => "Chu" ] ] ] ] ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1665642313715438?idApp=UINPBA00004N" "url" => "/16656423/0000001100000003/v2_201505081636/S1665642313715438/v2_201505081636/en/main.assets" ] "en" => array:16 [ "idiomaDefecto" => true "titulo" => "Dynamic Self-Assessment of Supply Chains Performance: an Emerging Market Approach" "tieneTextoCompleto" => true "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "338" "paginaFinal" => "347" ] ] "autores" => array:1 [ 0 => array:3 [ "autoresLista" => "M. Cedillo-Campos, C. Sánchez-Ramírez" "autores" => array:2 [ 0 => array:4 [ "nombre" => "M." "apellidos" => "Cedillo-Campos" "email" => array:1 [ 0 => "gaston.cedillo@mexico-logistico.org" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">1</span>" "identificador" => "aff0005" ] ] ] 1 => array:3 [ "nombre" => "C." "apellidos" => "Sánchez-Ramírez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">2</span>" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:2 [ 0 => array:3 [ "entidad" => "Department of Logistics and Supply Chain Management Universidad Autónoma de Nuevo León (UANL) Av. Universidad s/n. Ciudad Universitaria, C.P. 6645 San Nicolás de los Garza, Nuevo León, Mexico" "etiqueta" => "1" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Division of Research and Postgraduate Studies Instituto Tecnológico de Orizaba Av. Oriente 9, 852. Col Emiliano Zapata C.P. 94320 Orizaba, Veracruz, Mexico" "etiqueta" => "2" "identificador" => "aff0010" ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "f0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 781 "Ancho" => 1555 "Tamanyo" => 71043 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0005" class="elsevierStyleSimplePara elsevierViewall">Causal Loop Diagram of the Distribution Process.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">1</span><span class="elsevierStyleSectionTitle" id="sect0020">Introduction</span><p id="par0010" class="elsevierStylePara elsevierViewall">For many years, Mexico has been one of the most competitive places for investment in the manufacturing industry, mainly for automotive corporations in quest of new marketplaces and strengthening their presence in America. The country’s geographical location and 44 international free trade agreements provide an important platform to deliver products from Mexico to many countries in the world. Recently, Mexico has been targeted by automotive companies as Audi, Mazda, Honda, Fiat and Chinese companies as a key location in their internationalization strategy (<a class="elsevierStyleCrossRef" href="#bib0005">Deloitte, 2010</a>; <a class="elsevierStyleCrossRef" href="#bib0010">OICA, 2010</a>).<a name="p339"></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">Essentially, the automotive sector has a significant rate of product innovation because of the fierce competition between manufacturers for a mature market and importance to position themselves within the new trends in customer demand for the coming years (<a class="elsevierStyleCrossRef" href="#bib0005">Deloitte, 2010</a>). The presence of this industry has grown strongly in countries such as USA, Japan, Germany, France and Italy, mature markets that have had so far a major role in this industry, defining the policies of the performance of this industry (<a class="elsevierStyleCrossRef" href="#bib0015">Humphrey, Memedovic, 2003</a>). However, a growth in emerging economies like South Korea, China, India, Brazil, Mexico, Thailand and Malaysia has been seen in recent years, which will be a reference to this sector in the future (<a class="elsevierStyleCrossRef" href="#bib0020">Mukherjee, Sastry, 1996</a>; <a class="elsevierStyleCrossRef" href="#bib0025">Langley, 2012</a>). The evolution of this industry is also reflected in their production systems, which have gone from “make-to-stock”, where standardization of the products was the main goal, to “make-to-order”, which seeks efficiency in production systems, paying attention to changing market demands (<a class="elsevierStyleCrossRef" href="#bib0030">Meyr, 2004</a>). This will certainly impact the development of their innovation strategies, manufacturing processes and supply chain performance. In this context, the purpose of this paper is to provide a decision support aid through a dynamic self-assessment of the performance tool. To this end, we have identified well-established key performance indicators (KPI) and their dynamic relationships in order to facilitate the dynamic measurement of their impact on supply chain performance.</p><p id="par0020" class="elsevierStylePara elsevierViewall">This article is structured as follows: <a class="elsevierStyleCrossRef" href="#sec0010">Section 2</a> presents the importance of supply chains, highlighted as a success factor in the automotive sector. <a class="elsevierStyleCrossRef" href="#sec0025">Section 3</a> provides the model description and its casual loop diagrams and equations that support the dynamic hypothesis. <a class="elsevierStyleCrossRef" href="#sec0030">Section 4</a> exposes the system dynamics (SD) simulation and the validation process using design of experiments. Finally, in <a class="elsevierStyleCrossRef" href="#sec0045">Section 5</a>, conclusions as well as future research work will be presented.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2</span><span class="elsevierStyleSectionTitle" id="sect0025">Background</span><p id="par0025" class="elsevierStylePara elsevierViewall">In a changing economic world, new performance processes, machineries and manufacturing systems will need new methods and decision support aids. Furthermore, innovative tools are needed in support of customization and “make-to-order” strategies in automotive, electronics and aerospace industries. Dynamic measuring systems for exact and time efficient measurement combined with adaptive automated tool-control are a possible solution to support just-in-sequence approaches in the near future (<a class="elsevierStyleCrossRef" href="#bib0035">Wagner, Silveira-Camargos, 2011</a>). Therefore, as manufacturing develops global capabilities, the core of competition will no longer be only between supply chains but between regional industrial clusters too. In this sense, a wider logistics concept is proposed by <a class="elsevierStyleCrossRef" href="#bib0040">Cedillo-Campos (2012)</a> which is called <span class="elsevierStyleItalic">supply chain clustering</span>. It links the advantages of theoretical and practical developments in the supply chain area as well as in the industrial cluster domain from a geographical standpoint. It is a new management and engineering concept to improve business cluster based on supply chain competitiveness from a global-local perspective. In sophisticated supply chain clustering systems such as Silicon Valley, regional competitiveness as well as supply chain performance are improved at a highest level (<a class="elsevierStyleCrossRef" href="#bib0045">Saxenian, 1994</a>; <a class="elsevierStyleCrossRef" href="#bib0050">Cedillo-Campos and Pérez-Araos, 2010</a>). Actually, the geographical component of supply chain will be more and more a key element of industrial competitiveness (<a class="elsevierStyleCrossRef" href="#bib0080">Bhatnagar and Sohal, 2005</a>; <a class="elsevierStyleCrossRef" href="#bib0060">Rodriguez, 2012</a>).</p><p id="par0030" class="elsevierStylePara elsevierViewall">Furthermore, increased growth of the North American Trade Agreement (NAFTA) integration is expected based on supply chain flows boosted by the automotive industry and also by the electronic and aerospace industry. A “reverse globalization” is becoming a trend as firms back off from China to other countries such as Mexico for sourcing and manufacturing operations. Analysis from the Boston Consulting Group (BCG) identifies that the move offshore to China by U.S. corporations seeking lower labor costs may slow considerably over the next few years and even reverse path, as rising wages in China will make it more expensive to the U.S., when productivity gaps are factored in (<a class="elsevierStyleCrossRef" href="#bib0065">SCD, 2011</a>; <a class="elsevierStyleCrossRef" href="#bib0070">2012</a>). The opportunity to organize inside the NAFTA area one of the largest regional manufacturing zones in the world exists; however, because of the intensification of operations, improving measurement of supply chain performance will be a critical issue for manufacturing companies.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Since demand and supply structures fluctuate, a manufacturing supply chain must be adjusted over the product life cycle if a business tries to continuously achieve dynamic competitiveness. In <a name="p340"></a>fact, a number of researchers have already studied supply chains and their importance regarding the competitive advantages for companies and regions (<a class="elsevierStyleCrossRef" href="#bib0040">Cedillo-Campos, 2012</a>; <a class="elsevierStyleCrossRef" href="#bib0045">Saxenian, 1994</a>; <a class="elsevierStyleCrossRef" href="#bib0080">Bhatnagar, and Sohal, 2005</a>; <a class="elsevierStyleCrossRef" href="#bib0060">Rodriguez, 2012</a>; <a class="elsevierStyleCrossRef" href="#bib0075">Cedillo-Campos, Sánchez and Sánchez, 2006</a>; <a class="elsevierStyleCrossRef" href="#bib0080">Bhatnagar and Sohal, 2005</a>).</p><p id="par0040" class="elsevierStylePara elsevierViewall">In assembly industries, supply chain solution approaches are a key element to success because of the quantity of components, process and organizations needed to make a vehicle. Thus, it becomes a strategic issue for the performance and permanence of companies in a market that is increasingly globalized and competitiveness propagating uncertainty all along automotive supply chains (<a class="elsevierStyleCrossRef" href="#bib0085">Duggan, 2008</a>; <a class="elsevierStyleCrossRef" href="#bib0090">Knemeyer, Zinn, Eroglu, 2009</a>; <a class="elsevierStyleCrossRef" href="#bib0095">Sánchez, Cedillo-Campos, Pérez, Martínez, 2011</a>; <a class="elsevierStyleCrossRef" href="#bib0100">Chopra and Meindl, 2012</a>; <a class="elsevierStyleCrossRef" href="#bib0105">Waters, 2003</a>).</p><p id="par0045" class="elsevierStylePara elsevierViewall">Even if it is not a new phenomenon, concluding solutions have not been proposed until now. In fact, <a class="elsevierStyleCrossRef" href="#bib0110">Forrester (1961)</a> conducted the first analysis, from a dynamic and comprehensive point of view, which was aimed to demonstrate the phenomenon of demand amplification and its impact on the links that make up the supply chain. Recently, <a class="elsevierStyleCrossRef" href="#bib0115">Jimenez et al. (2002)</a>, <a class="elsevierStyleCrossRef" href="#bib0120">Cedillo-Campos et al. (2008)</a>, and <a class="elsevierStyleCrossRef" href="#bib0095">Sanchez et al. (2011)</a> identified the close relationship generated between dynamic oscillations in production systems and its impacts on supply chain processes operating under emerging markets conditions. They demonstrated the importance of systemic approaches to improve supply chain performance. Because of the complexity of considering different interrelated variables within a dynamic supply chain, the combined use of the system dynamics approach supported by the statistical method of design of experiments (DOE) provides a highly reliable analytic tool. In fact, <a class="elsevierStyleCrossRef" href="#bib0125">Kleijnen (1995)</a> and <a class="elsevierStyleCrossRef" href="#bib0130">GröBler et al. (2005)</a> consider that this approach offers a middle ground between pure formal modeling, and empirical observations and experiments, with high reliability in the analysis.</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2.1</span><span class="elsevierStyleSectionTitle" id="sect0030">System dynamics methodology</span><p id="par0050" class="elsevierStylePara elsevierViewall">In our research, system dynamics was used as the application of feedback control systems to the supply chain field. The SD approach pursues to integrate the functional units of an organization into a whole system and deliver quantitative data for measuring and designing more effective supply chains. From a SD point of view, the performance of a supply chain results mainly from its organization structure where the organization structure includes tangible decision aspects about facility location or manufacturing processes, for instance, but more importantly, from the procedures and behaviors that govern organizational decision-making processes. This framework includes sources of amplification, time lags, and information feedback related to complex supply chain engineering (<a class="elsevierStyleCrossRef" href="#bib0135">Roberts, 1978</a>). In this research the structural orientation of system dynamics provides a better understanding of this complexity.</p></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">2.2</span><span class="elsevierStyleSectionTitle" id="sect0035">Design of experiments</span><p id="par0055" class="elsevierStylePara elsevierViewall">As for design of experiments, it is a useful statistical tool for supply chain engineers faced with understanding the relation between numerous variables and one or more response variables in the context of optimizing a manufacturing process or redesigning a supply chain. Design of experiments is a valuable approach for leading the most effective experiments and understanding the outcomes using statistical procedures (<a class="elsevierStyleCrossRef" href="#bib0140">Montgomery, 2012</a>).</p><p id="par0060" class="elsevierStylePara elsevierViewall">A key component of design of experiments is operationalization, which is the formal procedure that links scientific concepts to data collection. In this sense, operationalizations define measures or variables which are quantities of interest or which serve as the practical substitutes for the concepts of interest. In this research, design of experiments provides a significant balance of several features including generalizability, various forms of “validity”, practicality, and reduced cost of analysis.</p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">3</span><span class="elsevierStyleSectionTitle" id="sect0040">Model description</span><p id="par0065" class="elsevierStylePara elsevierViewall">In order to study complex system dynamics, causal diagrams are an essential element to establish the problem to be analyzed. According to <a class="elsevierStyleCrossRef" href="#bib0145">Oliva (1996)</a>, the causal loop diagrams are the dynamic hypothesis that allows explaining how the structure of the system can modify its behavior. In this section, we establish the dynamic hypothesis of the proposed model, identifying the main feedback loops between the systems variables (KPI).</p><p id="par0070" class="elsevierStylePara elsevierViewall">In our model, the <span class="elsevierStyleBold"><span class="elsevierStyleItalic">distribution process</span></span> (see <a class="elsevierStyleCrossRef" href="#f0005">Figure 1</a>) has three important variables which are i) <a name="p341"></a>finished good inventory (<span class="elsevierStyleItalic">FGI</span>), ii) order backlog (<span class="elsevierStyleItalic">OB</span>), and iii) shipping to customer (<span class="elsevierStyleItalic">SC</span>). The loop (<span class="elsevierStyleBold">R1</span>) that is composed by these variables, represents a behavior in which if the inventory of finished goods is greater or equal to the customer’s order that must be reached, it is sent to the customer so that each increase inventory of finished goods will increase the rate of shipments to customers and vice versa.</p><elsevierMultimedia ident="f0005"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">The balancing loop (<span class="elsevierStyleBold">B1</span>) represents a performance where if the finished goods inventory increases, then the shipping rate will also increase, but if there is an increase in shipments, the inventory of finished goods will decrease. The equations for this subsystem are as follows:</p><p id="par0080" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0005"></elsevierMultimedia></p><p id="par0085" class="elsevierStylePara elsevierViewall">Where w=1, …, 52. Thus, customer demand is received every week. However, since they must be waiting for being scheduled and produced, an <span class="elsevierStyleItalic">OB</span> is caused, which is calculated as follows:</p><p id="par0090" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0010"></elsevierMultimedia></p><p id="par0095" class="elsevierStylePara elsevierViewall">Where <span class="elsevierStyleItalic">CD</span> is the Customer Demand and <span class="elsevierStyleItalic">SC</span> is calculated by the minimum value between <span class="elsevierStyleItalic">OB</span> and <span class="elsevierStyleItalic">FGI</span>, computed as follows:</p><p id="par0100" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0015"></elsevierMultimedia></p><p id="par0105" class="elsevierStylePara elsevierViewall">At the same time, orders that have been produced (<span class="elsevierStyleItalic">P</span>) are shipped to <span class="elsevierStyleItalic">FGI</span>, which is calculated by</p><p id="par0110" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0020"></elsevierMultimedia></p><p id="par0115" class="elsevierStylePara elsevierViewall">In the <span class="elsevierStyleBold"><span class="elsevierStyleItalic">production process</span></span> subsystem (see <a class="elsevierStyleCrossRef" href="#f0010">Figure 2</a>), if the production rate is increased, the inventory of finished goods does as well. In addition, by increasing the inventory, the rate of shipments to customers will also be higher and thus may reduce the order backlog. However, an increase in outstanding orders would positively influence the order production, therefore, orders would increase in the queue and this, in turn, would positively influence in the same way the production (<span class="elsevierStyleBold">B2</span>).</p><elsevierMultimedia ident="f0010"></elsevierMultimedia><p id="par0120" class="elsevierStylePara elsevierViewall">In the production process subsystem, the orders received are considered as order production (<span class="elsevierStyleItalic">OP</span>) which is calculated by the following equation:</p><p id="par0125" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0025"></elsevierMultimedia></p><p id="par0130" class="elsevierStylePara elsevierViewall">Production schedule (<span class="elsevierStyleItalic">PS</span>) allocates a level of priority to customer orders (1, 2 or 3), which is assigned according to a FIFO (first input, output first) queuing process technique by ordering the process by first customer’s order arrived (priority 1), first-served. In this sense, adjustment of finished good inventory (<span class="elsevierStyleItalic">AFGI</span>) serves to correct the difference between <span class="elsevierStyleItalic">FGI</span> and the desired inventory of finished goods (<span class="elsevierStyleItalic">DIFG</span>) in a period of time which is allocated by adjustment time of desired inventory (<span class="elsevierStyleItalic">ATDI</span>). The calculation of this adjustment is realized by the following expression:</p><p id="par0135" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0030"></elsevierMultimedia></p><p id="par0140" class="elsevierStylePara elsevierViewall">Thus, production (<span class="elsevierStyleItalic">P</span>) takes the minimum value between <span class="elsevierStyleItalic">RMI</span>, <span class="elsevierStyleItalic">PC</span> and <span class="elsevierStyleItalic">PS</span> and is calculated by</p><p id="par0145" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0035"></elsevierMultimedia></p><p id="par0150" class="elsevierStylePara elsevierViewall">Where <span class="elsevierStyleItalic">PC</span> is the production capacity, <span class="elsevierStyleItalic">RMI</span> is the raw material inventory and <span class="elsevierStyleItalic">PS</span> is the production schedule.</p><p id="par0155" class="elsevierStylePara elsevierViewall">In the <span class="elsevierStyleBold"><span class="elsevierStyleItalic">procurement process</span></span> (see <a class="elsevierStyleCrossRef" href="#f0015">Figure 3</a>), the system behaves in such a way that if the inventory increases, then compliance with production orders increases, but this increase in production orders influences the decreasing inventory of raw material (<span class="elsevierStyleBold">B3</span>). Likewise, if production orders increase, then the number of orders made to suppliers increases (<span class="elsevierStyleBold">B4</span>), and this will increase traffic orders. If orders in transit increase, the inventory level of raw material will increase, impacting the supply to production orders in the same way (<span class="elsevierStyleBold">B5</span>).</p><elsevierMultimedia ident="f0015"></elsevierMultimedia><p id="par0160" class="elsevierStylePara elsevierViewall">The <span class="elsevierStyleBold"><span class="elsevierStyleItalic">RMI</span></span> is calculated as follows:</p><p id="par0165" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0040"></elsevierMultimedia></p><p id="par0170" class="elsevierStylePara elsevierViewall">Where <span class="elsevierStyleItalic">OT</span> is orders in transit which is influenced by the delivery time (<span class="elsevierStyleItalic">DT</span>) and orders, which are generated by the following equation:</p><p id="par0175" class="elsevierStylePara elsevierViewall"><elsevierMultimedia ident="eq0045"></elsevierMultimedia></p><p id="par0180" class="elsevierStylePara elsevierViewall">Where, <span class="elsevierStyleItalic">RP</span> is the reorder point and <span class="elsevierStyleItalic">LS</span> is lot size.<a name="p342"></a><a name="p343"></a></p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">4</span><span class="elsevierStyleSectionTitle" id="sect0045">Analysis and results</span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">4.1</span><span class="elsevierStyleSectionTitle" id="sect0050">Evaluation of the proposed model</span><p id="par0185" class="elsevierStylePara elsevierViewall">The implementation of the system was validated within a key automotive company with global operations. For the first scenario, for testing the system, 1,000 pieces of customer #1 were scheduled at 7:00 a.m. The scheduled delivery date was two days (48 hours). In this case, customer #2’s and #3’s orders were not scheduled.</p><p id="par0190" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the initial data and the results obtained in the simulation of this scenario. The simulation time horizon was one week (168 hours). Orders were fulfilled in 100% of the cases and demand of customer # 1 was served.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0195" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#f0020">Figure 4</a> shows an increase at the moment the request is scheduled. The inventory behavior of finished goods is also analyzed when it is sent to the customer, and 125 pieces remain in the inventory of finished goods.</p><elsevierMultimedia ident="f0020"></elsevierMultimedia></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">4.1</span><span class="elsevierStyleSectionTitle" id="sect0055">Validation based on design of experiments</span><p id="par0200" class="elsevierStylePara elsevierViewall">Authors such as <a class="elsevierStyleCrossRef" href="#bib0150">Forrester and Senge (1980)</a>, <a class="elsevierStyleCrossRef" href="#bib0155">Barlas (1996)</a>, <a class="elsevierStyleCrossRef" href="#bib0160">Kleijnen (1992)</a> and <a class="elsevierStyleCrossRef" href="#bib0165">Umeda and Jain (2004)</a> suggest the application of techniques such as sensitivity analysis, linear regression and design of experiments for the validation of systems developed in system dynamics. However, it is important to note that few authors validate their systems using these techniques given that most of them validate the system according to the system structure and behavior.</p><p id="par0205" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a> presents data obtained for the development of the design of experiments, of which three replicas were made. The factors considered were</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0210" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">(A) Inventory of Finished Goods: 1000 (-) a 3000 (+) Pcs.;</span></span></p><p id="par0215" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">(B) Work In Process (WIP): 500 (-) a 1000 (+) Pcs.;</span></span></p><p id="par0220" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold"><span class="elsevierStyleItalic">(C) Production Capacity: 100 (-) a 400 (+) Pcs / hr.</span></span></p><p id="par0225" class="elsevierStylePara elsevierViewall">The results obtained from the runs in STELLA® were integrated into MINITAB® version 15 to analyze the design of experiments and to identify significant factors in the logistics evaluation system.</p><p id="par0230" class="elsevierStylePara elsevierViewall">The results obtained in the ANOVA (<a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a>) indicate that the <span class="elsevierStyleItalic">inventory of finished goods, work in process and production capacity</span> influence the fulfillment of orders. Combinations A * C and B * C are also significant, but the combination of the factors A * B and the combination of the three factors A * B * C are not significant. The coefficient of multiple determination R<span class="elsevierStyleSup">2</span> (99.23%) and the adjusted R<span class="elsevierStyleSup">2</span> (98.90%) are measures of regression analysis and allow explaining the system’s good fit.<a name="p344"></a><a name="p345"></a></p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia></span></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleLabel">5</span><span class="elsevierStyleSectionTitle" id="sect0060">Conclusions and future work</span><p id="par0235" class="elsevierStylePara elsevierViewall">The main contribution of this study leads to several important insights for manufacturing firms that participate in complex and dynamic assembling industries such as the automotive one. Faced with the hypercompetitive economic context organized in the automotive networks, it is not only necessary to have better organized logistics processes, but it is also necessary to integrate dynamically the set of differentiated advantages with which local actors (suppliers, manufacturers, logistics providers, etc.) can contribute to the competitiveness of any industrial system (<a class="elsevierStyleCrossRef" href="#bib0100">Chopra and Meindl, 2012</a>; <a class="elsevierStyleCrossRef" href="#bib0105">Waters, 2003</a>).</p><p id="par0240" class="elsevierStylePara elsevierViewall">Our analysis not only identified the key logistics variables and its relationship, its pertinence was also verified through a DOE analysis. Since our model presents the key variables from a general point of view, manufacturers in emergent markets should identify their specific key operational logistics variables in order to focus their efforts on developing dynamic capabilities from a more global-local approach.</p><p id="par0245" class="elsevierStylePara elsevierViewall">Through a hybrid approach, integrating a broad analysis allowed by system dynamics with the reliability provided by the design of experiments (DOE), it is feasible to analyze complex logistics processes. The ANOVA indicated that the model here proposed had a good fit, and at the same time, during the implementation process, decision makers provided positive feedback about the model as a reliable tool.</p><p id="par0250" class="elsevierStylePara elsevierViewall">As future work, the development of a more robust statistical analysis as well as other conducting tests and validation processes in different industrial systems are planned.<a name="p346"></a></p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres498777" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec520306" "titulo" => "Key words" ] 2 => array:3 [ "identificador" => "xres498776" "titulo" => "Resumen" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0010" ] ] ] 3 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 4 => array:3 [ "identificador" => "sec0010" "titulo" => "Background" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "System dynamics methodology" ] 1 => array:2 [ "identificador" => "sec0020" "titulo" => "Design of experiments" ] ] ] 5 => array:2 [ "identificador" => "sec0025" "titulo" => "Model description" ] 6 => array:3 [ "identificador" => "sec0030" "titulo" => "Analysis and results" "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0035" "titulo" => "Evaluation of the proposed model" ] 1 => array:2 [ "identificador" => "sec0040" "titulo" => "Validation based on design of experiments" ] ] ] 7 => array:2 [ "identificador" => "sec0045" "titulo" => "Conclusions and future work" ] 8 => array:2 [ "identificador" => "xack161137" "titulo" => "Acknowledgements" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Key words" "identificador" => "xpalclavsec520306" "palabras" => array:5 [ 0 => "supply chain" 1 => "performance measurement" 2 => "system dynamics" 3 => "automotive industry" 4 => "emerging markets" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">A dynamic self-assessment of performance on supply chains operating in emerging markets is proposed. Based on well-established key performance indicators (KPI), this paper provides a decision support aid. Although it has been validated in the automotive industry, the standardized model’s approach makes it applicable to other industries. It is the result of a large literature review and identification of best practices from the automotive industry in which the lack of dynamic tools to evaluate logistics performance of suitable supply chains to the current competitive exchange rate was detected. Developed under a system dynamics approach (DS), the model analyzes different scenarios taking into account KPI and its dynamic relationships. The results obtained were validated through the statistical technique of design of experiments (DOE). This model also considers the specific features of the automotive operations in emerging countries as well as their importance in the future development of the manufacturing industry. In this context, the tool exposed is a key backup to decision making and to dynamically evaluate the variables with major influence on manufacturing supply chains. As a conclusion, findings are discussed and future researches are presented.</p></span>" ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">Se propone un modelo para la autoevaluación dinámica del desempeño de cadenas de suministro operando en mercados emergente. Con base en indicadores de desempeño ampliamente establecidos en las operaciones industriales, se expone una herramienta de ayuda a la toma de decisiones. Aunque ha sido validado en el contexto de la industria automotriz, su enfoque estandarizado hace que sea aplicable a otras industrias. El modelo es el resultado de una amplia revisión de la literatura y de prácticas de la industria en donde se detectó la falta de herramientas dinámicas para evaluar el desempeño de las cadenas de suministro adecuadas a la evolución competitiva actual. El modelo, desarrollado bajo un enfoque de dinámica de sistemas (DS), analiza diferentes escenarios, teniendo en cuenta las variables dinámicas. Los resultados obtenidos fueron validados a través de la técnica de diseño de experimentos (DE). Este modelo también considera las características específicas de las operaciones automotrices en países emergentes, así como la importancia de estos mercados en el desarrollo futuro de la industria automotriz. En este contexto, la herramienta expuesta es un soporte clave para la toma de decisiones y para evaluar de forma dinámica las variables con mayor influencia en las cadenas de suministro automotrices. Como conclusión, los resultados son discutidos al mismo tiempo que se presentan futuras investigaciones.</p></span>" ] ] "multimedia" => array:16 [ 0 => array:7 [ "identificador" => "f0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 781 "Ancho" => 1555 "Tamanyo" => 71043 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0005" class="elsevierStyleSimplePara elsevierViewall">Causal Loop Diagram of the Distribution Process.</p>" ] ] 1 => array:7 [ "identificador" => "f0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 788 "Ancho" => 1671 "Tamanyo" => 98080 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0010" class="elsevierStyleSimplePara elsevierViewall">Causal Loop Diagram of the Production Process.</p>" ] ] 2 => array:7 [ "identificador" => "f0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 846 "Ancho" => 1702 "Tamanyo" => 78875 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0015" class="elsevierStyleSimplePara elsevierViewall">Causal Loop Diagram of the Procurement Process.</p>" ] ] 3 => array:7 [ "identificador" => "f0020" "etiqueta" => "Figure 4" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr4.jpeg" "Alto" => 678 "Ancho" => 1156 "Tamanyo" => 102408 ] ] "descripcion" => array:1 [ "en" => "<p id="sp0020" class="elsevierStyleSimplePara elsevierViewall">Graphical Analysis of Customer 1’s Demand.</p>" ] ] 4 => array:7 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Variable</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Initial Values</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Results</span> \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Customer Demand \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">1000 pcs. \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Orders Backlog \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">0 pcs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">0 pcs \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">WIP \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">0 pcs. \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">0 pcs. \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Inventory of Raw Material \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">15000 pcs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">13825 pcs \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Production Capacity \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">200 pcs/hr \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Inventory of Finished Goods \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">0 pcs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">125 pcs. \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Cycle Time \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">5 hrs \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">0 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Orders Fulfilled \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">- \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100% \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab796290.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Initial Values for Customer 1’s Demand.</p>" ] ] 5 => array:7 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Run</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">A</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">B</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">C</span> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " colspan="3" align="center" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Percentage of Orders Fulfilled (%)</span></th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">38 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">40 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">38 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">52 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">48 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">50 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">90 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">88 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">82 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">-</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">86 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="center" valign="top">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top"><span class="elsevierStyleBold">+</span> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="center" valign="top">100 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab796288.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Results Obtained From the Output of the Design 2<span class="elsevierStyleSup">3</span>.</p>" ] ] 6 => array:7 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " colspan="8" align="left" valign="top" scope="col" style="border-bottom: 2px solid black"><span class="elsevierStyleBold">Factorial Fit: EVALUACION versus A, B, C</span></th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Estimated Effects and Coefficients for EVALUACION (coded units)</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Term \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Effect \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Coef \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">SE Coef \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">T \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">P \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Constant \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">77.500 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">169.79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">A \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">28.667 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">14.333 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">31.40 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">B \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">5.333 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">2.667 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">5.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">27.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">13.500 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">29.58 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">A*B \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-0.333 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-0.167 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-0.37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.720 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">A*C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-10.667 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-5.333 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-11.63 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">B*C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-5.333 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-2.667 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">-5.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">A*B*C \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.333 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.167 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.4564 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.37 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.720 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">S = 2.23607</td><td class="td" title="table-entry " colspan="6" align="left" valign="top">PRESS = 180</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="2" align="left" valign="top">R-Sq = 99.23%</td><td class="td" title="table-entry " colspan="2" align="left" valign="top">R-Sq(pred) = 98.27%</td><td class="td" title="table-entry " colspan="4" align="left" valign="top">R-Sq(adj) = 98.90%</td></tr><tr title="table-row"><td class="td" title="table-entry " colspan="8" align="left" valign="top">Analysis of Variance for EVALUACION (coded units)</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Source \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">DF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Seq SS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Adj SS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Adj MS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">F \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">P \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Main Effects \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">9475.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">9475.33 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">3158.44 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">631.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">2-Way Interactions \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">854.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">854.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">284.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">56.93 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.000 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">3-Way Interactions \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.13 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">0.720 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Residual Error \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">80.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">80.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">5.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top"><span class="elsevierStyleHsp" style=""></span><span class="elsevierStyleHsp" style=""></span>Pure Error \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">16 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">80.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">80.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">5.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">23 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="right" valign="top">10410.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab796289.png" ] ] ] ] "descripcion" => 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Year/Month | Html | Total | |
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2024 October | 23 | 8 | 31 |
2024 September | 13 | 6 | 19 |
2024 August | 15 | 2 | 17 |
2024 July | 10 | 4 | 14 |
2024 June | 19 | 4 | 23 |
2024 May | 25 | 2 | 27 |
2024 April | 22 | 2 | 24 |
2024 March | 25 | 7 | 32 |
2024 February | 10 | 3 | 13 |
2024 January | 30 | 8 | 38 |
2023 December | 33 | 7 | 40 |
2023 November | 25 | 5 | 30 |
2023 October | 31 | 9 | 40 |
2023 September | 10 | 4 | 14 |
2023 August | 26 | 3 | 29 |
2023 July | 21 | 5 | 26 |
2023 June | 40 | 6 | 46 |
2023 May | 69 | 6 | 75 |
2023 April | 62 | 7 | 69 |
2023 March | 53 | 8 | 61 |
2023 February | 50 | 1 | 51 |
2023 January | 28 | 4 | 32 |
2022 December | 53 | 11 | 64 |
2022 November | 50 | 4 | 54 |
2022 October | 89 | 13 | 102 |
2022 September | 52 | 5 | 57 |
2022 August | 44 | 13 | 57 |
2022 July | 25 | 5 | 30 |
2022 June | 35 | 6 | 41 |
2022 May | 22 | 13 | 35 |
2022 April | 21 | 11 | 32 |
2022 March | 45 | 9 | 54 |
2022 February | 40 | 2 | 42 |
2022 January | 82 | 4 | 86 |
2021 December | 28 | 12 | 40 |
2021 November | 32 | 9 | 41 |
2021 October | 39 | 18 | 57 |
2021 September | 47 | 33 | 80 |
2021 August | 28 | 5 | 33 |
2021 July | 18 | 11 | 29 |
2021 June | 8 | 11 | 19 |
2021 May | 24 | 6 | 30 |
2021 April | 56 | 26 | 82 |
2021 March | 58 | 6 | 64 |
2021 February | 27 | 8 | 35 |
2021 January | 20 | 9 | 29 |
2020 December | 19 | 8 | 27 |
2020 November | 19 | 8 | 27 |
2020 October | 10 | 5 | 15 |
2020 September | 17 | 9 | 26 |
2020 August | 24 | 9 | 33 |
2020 July | 15 | 1 | 16 |
2020 June | 15 | 3 | 18 |
2020 May | 18 | 3 | 21 |
2020 April | 9 | 4 | 13 |
2020 March | 22 | 10 | 32 |
2020 February | 11 | 5 | 16 |
2020 January | 8 | 1 | 9 |
2019 December | 15 | 7 | 22 |
2019 November | 11 | 5 | 16 |
2019 October | 16 | 2 | 18 |
2019 September | 19 | 0 | 19 |
2019 August | 11 | 1 | 12 |
2019 July | 20 | 3 | 23 |
2019 June | 49 | 27 | 76 |
2019 May | 131 | 9 | 140 |
2019 April | 66 | 8 | 74 |
2019 March | 9 | 3 | 12 |
2019 February | 18 | 4 | 22 |
2019 January | 12 | 2 | 14 |
2018 December | 10 | 2 | 12 |
2018 November | 14 | 0 | 14 |
2018 October | 12 | 2 | 14 |
2018 September | 5 | 8 | 13 |
2018 August | 5 | 11 | 16 |
2018 July | 3 | 9 | 12 |
2018 June | 5 | 6 | 11 |
2018 May | 11 | 12 | 23 |
2018 April | 10 | 7 | 17 |
2018 March | 11 | 5 | 16 |
2018 February | 9 | 3 | 12 |
2018 January | 15 | 1 | 16 |
2017 December | 16 | 1 | 17 |
2017 November | 6 | 5 | 11 |
2017 October | 15 | 5 | 20 |
2017 September | 6 | 17 | 23 |
2017 August | 10 | 12 | 22 |
2017 July | 8 | 4 | 12 |
2017 June | 54 | 35 | 89 |
2017 May | 17 | 11 | 28 |
2017 April | 7 | 21 | 28 |
2017 March | 7 | 74 | 81 |
2017 February | 9 | 2 | 11 |
2017 January | 8 | 2 | 10 |
2016 December | 12 | 10 | 22 |
2016 November | 26 | 3 | 29 |
2016 October | 33 | 6 | 39 |
2016 September | 19 | 2 | 21 |
2016 August | 23 | 3 | 26 |
2016 July | 11 | 1 | 12 |
2016 June | 22 | 14 | 36 |
2016 May | 9 | 6 | 15 |
2016 April | 26 | 10 | 36 |
2016 March | 18 | 10 | 28 |
2016 February | 17 | 6 | 23 |
2016 January | 15 | 9 | 24 |
2015 December | 43 | 7 | 50 |
2015 November | 16 | 0 | 16 |
2015 October | 16 | 5 | 21 |
2015 September | 17 | 3 | 20 |
2015 August | 26 | 3 | 29 |
2015 July | 13 | 3 | 16 |
2015 June | 2 | 0 | 2 |
2015 May | 7 | 2 | 9 |
2015 April | 5 | 1 | 6 |