Indicators for the facility layout design in MSMEs in the textile se= ctor with a resilient approach

Indicadores para el diseńo de distribución de planta en MiPymes del sector Textil con un enfoque resiliente

¹=	José Andrés Albán Palango.	https://orcid.org/0000-0003-3640-8158
<= /span>	Universidad Técnica de Ambato, Facultad de Ingeniería en Sistemas Electrónica e Industrial, Carrera de Ingeniería Industrial, Ambato, Ecuador<= /span> jalban0095@uta.edu.ec
= ²=	Franklin Geovanny Tigre Ortega. =	https://orcid.org/000= 0-0003-0254-029X
<= /span>	Universidad Técnica de Ambato, Facultad de Ingeniería en Sistemas Electrónica e Industrial, Carrera de Ingeniería Industrial, Ambato, Ecuador<= /span> fg.tigre@uta.edu.ec
= ³=	Freddy Roberto Lema Chicaiza.	https://orcid.org/0000-0001-5987-8975=
<= /span>	Universidad Técnica de Ambato, Facultad de Ingeniería en Sistemas Electrónica e Indus= trial, Carrera de Ingeniería Industrial, Ambato, Ecuador fr.lema@uta.edu.ec

=	Artículo de Investigación Científica y Tecnológi= ca Enviado: 05/01/2022 Revisado: 20/01/2022 Aceptado: 07/02/2022 Publicado:05/04/2022 DOI: https://doi.org/1= 0.33262/concienciadigital.v5i2.2115 = <= /u> &= nbsp;

Cítese:		Albán Palango, J. A., Tigre Ortega, F. G., & Lema Chicaiza, F.= R. (2022). Indicators for the facility layout design in MSM= Es in the textile sector with a resilient approach . ConcienciaDigital, 5(2), 17-40= . https://doi.org/10.33262/conci= enciadigital.v5i2.2115
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Palabr= as claves: = problema de distribución de instalaciones, resiliencia, revisión literaria, MiPymes textiles, indicadores. &= nbsp;	&= nbsp;	Resumen = Introducción. La capacidad de respuesta y adaptación a los riesgos y problemas de una organización es fundamental para el éxito empresarial. Cualquier tipo de debilidad provoca un uso ineficiente de los recursos. Por el contrario, u= nas instalaciones flexibles pueden garantizar la continuidad de las operacion= es ante eventos disruptivos, los cuales perjudican en gran medida a la empre= sa de no ser controlados, sin embargo, la flexibilidad no se consigue sólo c= on la optimización de las instalaciones, ya que los enfoques resilientes pue= den potenciarla. Objetivo. Sintetizar las variables e indicadores con mayor uso en tres diferentes ámbitos, la resiliencia empresarial, la industria textil y el problema de disposición de instalaciones (FLP). = Metodología. La investigación es de carácter bibliográfico-documental. Se desarrolló u= na revisión sistemática de la literatura, haciendo uso de la metodología Fin= k, considerando 99 estudios publicados entre el ańo 2010 y 2021. El análisis= de los documentos se lo realizó mediante el software Atlas.ti, posteriorment= e se usó un análisis 4W (cuándo, quién, qué y dónde), y finalmente se dieron respuesta a 3 preguntas de investigación planteadas mediante la estrategia PICO. Resultados. Los resultados indican que, existe una escasez de estudios sobre FLP resilientes, sin embargo, es notable que el interés científico en relación con la resiliencia ha aumentado en los últimos seis ańos, específicamente en los métodos y enfoques de evaluación para identificar los factores e indicadores de resiliencia en la industria a través de modelos matemáticos difusos. Conclusiones. Los estudios sobre resiliencia aplicada al FLP no son desarrollados en gran medida a n= ivel mundial, en el contexto ecuatoriano la resiliencia no ha sido profundizad= a. Finalmente se resalta la importancia de los indicadores para un modelo preciso y se propone una serie de indicadores para el análisis del comportamiento del diseńo de instalaciones con un enfoque resiliente basa= do en factores FLP.
Keywords: Facility layout problem, Resilience, Literature review, Textile SM= Es, Indicators. &= nbsp;	&= nbsp;	Abstract= Introduction= . The capacity to respond and adapt to the risks = and problems in an organization is critical for business success. Any type of weakness causes inefficient use of resources. On the contrary, flexible facilities can ensure the continuity of operations in the face of disrupt= ive events, which significantly harm the company if they are not controlled. However, flexibility is not achieved only with the optimization of facilities, as resilient approaches can enhance it. Objective. To synthesize the variables and indicators with greater use in three differe= nt areas, business resilience, the textile industry, and the facility layout problem (FLP) in the textile industry. Methodology. The research i= s of a bibliographic-documentary nature. A systematic literature review was conducted, using the Fink methodology, considering 99 studies published between 2010 and 2021. The documents were analyzed using the Atlas.ti software; subsequently, a 4W (when, who, what, and where) analysis was us= ed; finally, answers were given to three research questions posed through the PICO strategy. Results. The findings indicate that, there is a scarcity of studies about resilient FLPs, however, it is notable that the scientific interest regarding resilience has increased in the last six ye= ars, specifically in assessment methods and approaches to identify resilience factors and indicators in the industry through fuzzy mathematical models.= Conclusions. Studies about resilience applied to FLP are not developed to a great exte= nt worldwide, in the Ecuadorian context resilience has not been explored in depth. Eventually, the importance of indicators for an accurate model is highlighted and a series of indicators for the analysis of the behavior o= f facility layout with a resilient approach based on FLP factors is proposed.

Introduction

= The need for companies to adapt to an uncertain fu= ture represents a challenge, primarily due to the pandemic caused by Covid-19 (Moosavi & Hosseini, 2021). This has generated abrupt changes, resulting in a challenging competitive environment in the areas of price, quality, time and innovation. As a resul= t, organizations focus their attention on achieving the appropriate levels in = the aforementioned areas. Unfortunately, companies’ strategies have been obsole= te or inefficient (Carvajal et al., 2018). This is most evident in small and medium-sized enterprises (SMEs), whose response to the unpredictable nature of the sanitary crisis has been affect= ed by their limited resources (Moosavi & Hosseini, 2021; Ugail et al., 2021). In addition, these types of organizations are one of the main integrators of economic growth, creating job opportunities and helping them to become contributors to large companies such as suppliers of goods and services. SM= Es represent over 70 % of world production, so that a considerable drop in the= ir production would represent a major impact on the economy, making the development and implementation of change strategies essential for them to remain in a highly competitive environment (Ates & Bititci, 2011).

Because of the limited innovation and implementati= on of new methodological tools, Ecuador has experienced a great impact on the industrial sector, as processes have not been able to be managed properly, generating greater difficulty for organizations to remain active (Villalba et al., 2018). At the national level, the textile industry is one of the most important, b= eing considered as the second productive axis of the country, however, the texti= le sector and other sectors such as footwear present adaptability problems to = this type of situation due to the highly dynamic nature of their processes. For = this reason, it is of utmost importance that organizations use different methodologies or tools that provide an optimal solution to the problems and risks generated in these industries (Ramos et al., 2018; Zhao & Kim, 2021).

One of these necessary tools for companies is the facility layout since through this tool, it is possible to optimally design= the physical space, following a series of criteria under certain restrictions, = such as shape, size, orientation, or availability (Hosseini-Nasab et al., 2018). Moreover, flexibility in the industries is anoth= er key point to improve their performance and provide adequate responses to different adversities. In this sense, the facility layout problem (FLP) fits somewhat into these flexibility requirements (Flores et al., 2021). However, plant designs do not always react adequately under unfavorable circumstances, generating instabilities and failures in activities. Thus, adapting to critical events with positive res= ults has become an intrinsic necessity (Tayal & Singh, 2019). In situations like this, resilience plays a cruc= ial role since its application allows organizations to anticipate their respons= es to perturbations and react before, during, and after a problem (Thoma et al., 2016). Several authors have studied the concept of resilience from different perspectives. However, this study concerns resili= ence engineering, defined as the capacity of an organization to adapt to critical events or threats, i.e., constantly anticipating risks before their consequences affect the company (Flores, 2021; Shirali et al., 2013).

FLP and Resilience can face several strategic challenges; unfortunately, the research that refers to the interaction of b= oth subjects is scarce (Navazi et al., 2021). Therefore, the relevance of resilience studies focuses on analyzing methods for its measurement, considering a series of variables and indicators. The different studies on the subject support this statement. For example, Bevilacqua et al. (2020) study the supply chain through fuzzy cognitive ma= ps to analyze the domino effect of resilience inhibitors. In the same line Macuzić et al. (2016), propose a two-step fuzzy mathematical model to classify resilience factors in the process industry. = In both cases, it is emphasized that resilience factors allow better managemen= t of organizations.

= FLP focuses its interest on the optimum use of physical space, considering factors such as material flow, equipment utilization, process times, and, in general, the minimization of costs rela= ted to production (Perez, 2016). Nevertheless, FLP studies generally ignore certain elements such as top management, learn= ing culture, communication, or teamwork, causing the design and monitoring of a plant layout to leave aside a series of features necessary to overcome poss= ible disruptions (Azadeh et al., 2014b). This is evidenced in the proposal of Diego-Mas et al. (2009), which exposes geometric restrictions. They use a two-phase genetic algorith= m to solve facility design problems, considering only FLP dependent indicators, = such as the material handling, falling back on the one-dimensional use of measur= ing the efficiency of a cost-based plant layout model. On the contrary, an important factor in the study of resilience and FLP is the focus of the pro= posed indicators for monitoring and evaluating the designs.

Using indicators other than the traditional employ= ed in facility layout designs allows better integration of the flexibility mentioned above. For example, Azadeh and Moradi (2014) present a fuzzy simulation algorithm for facility design. In this study, sa= fety and ergonomic factors are considered metrics and restrictions in searching = for the optimal model. The authors also used indicators such as average queue waiting time, average system time, and average machine utilization, in addi= tion to FLP-dependent indicators. Therefore, integrating indicators for plant la= yout design with a resilient approach requires an analysis of the elements and v= ariables used in the three dimensions, i.e., resilience, textile industry, and plant layout design. However, combining all aspects of each dimension in a single conceptual framework of indicators is a highly challenging task (Raman et al., 2009). Unfortunately, the literature has not explored the relationship between resilience and FLP (Flores et al., 2021; Raman et al., 2009).

The purpose of this article consists of an analysi= s of the resilience factors and variables used in the industry, followed by a synthesis of the most relevant indicators in the textile sector, pointing o= ut its variables and elements. Finally, the relationship between resilience, textile sector indicators, and FLP is studied to obtain a list of indicators applicable to plant layout design with a resilient approach. This research contributes to the literature by introducing the indicators mentioned and guiding companies and researchers in understanding the current lines of research on resilience in the industry and indicators for FLP in the textile sector. The rest of the article is structured as follows. Section 2 describ= es the methodology used for the systematic literature search. Section 3 is constituted by the investigation results through the descriptive analysis of the information and a concise discussion. Finally, section 4 presents the m= ain conclusions.

Methodology

= The present research wo= rk uses the Fink methodology, which consists of seven steps to select relevant information systematically (Fink, 2019, pp. 3–5). In this manner, it is ensured that the resear= ch encompasses the resilience factors and indicators applied in designing the plant layout of MSMEs in the textile sector.

The first step of the F= ink method refers to selecting the research questions, for which the PICO strat= egy was used (Santos et al., 2007), determining the Population, Intervention, Comparison, and Outcomes related to the research. Thus, three questions were obtained: a) What variables or indicators are considered in a resilient mod= el in the textile industry? b) What variables or indicators are used in the textile industry? c) What variables or indicators can be used in a resilient approach for a plant layout design in SMEs in the textile sector?

As for Step 2, the definition of database sources, Scopus and Web of Science, were used for academic articles. Due to the need to integrate studies in which textile industry indicators and FLP indicators are applied, LA Reference and RRAAE repositories were used for theses. For Step 3, selection of search terms, 1= 2-character strings were selected, which respond to the research questions. These strin= gs were: “Resilience” AND “Industry”, (“Industry” AND “Textile” AND “Indicator= s”) OR (“Indicator” OR “Indicators”) AND “Textile”, “Industry” AND “Resilience”= AND “Indicators”, “Distribution problems” AND “Indicators” AND “Industry”, “Resilience” AND “Industry” AND “Textile”, “Resilience” AND “Indicators” AND “Facility layout problems”, “Resilience” AND “Facility layout problems”, “Indicators” AND “Facility layout problems”, “Resilient facility location”, “Standard” AND ("Facility Layout" OR "Plant Design" OR "Plant Layout") AND Textile", "Standard" AND ("Facility Layout" OR "Plant Design" OR "Plant Layout"), ("Facility Layout" OR "Plant Design" OR "Plant Layout") AND ("Textile" OR "Confection"= ;).

Applying practical and methodological selection criteria from Steps 4 and 5 facilitates the search= es to provide relevant results following the research topic. In this manner, t= he literature review guarantees that the articles and theses collected are relevant and current. Therefore, the following criteria were considered for their inclusion: 1) theoretical or applied articles and theses written in Spanish and English; 2) scientific journals articles; 3) articles and theses published between 2010 and 2021; 4) subject areas: Engineering, Management, Production, Mathematics, Decision Sciences, Economics, and Econometrics. In addition, the following exclusion criteria were used: 1) irrelevant article= s, 2) duplicate articles, and 3) articles with comments from academic publications.

The documents that satisfied the exclusion criteria answered the following questions: Has the research design internal and external validity? Is reliability and validity present in the databases used? Are the analytical methods adequate to the characteristics and quality of the research data? The methodological qualit= y of the documents found decreased if they did not answer one or more questions.= The review of the documentation corresponding to Step 6 was carried out qualita= tively using the Atlas.ti software, in which 53 codes were established to highlight and classify the information.

Finally, the results we= re synthesized in Step 7. The number of documents obtained after the review and application of the search methodology is summarized in Table 1. As can be s= een, there are 99 research studies, of which 59 correspond to articles and 40 to theses. In addition, 26 studies have been identified that addressed issues related to textile industry indicators, 27 to FLP, and 46 referring to resilience in the industry.

Table 1

Application of practical and methodological selection criteria

Descripti= on	Articles<= o:p>	Theses	Total of documents	Excluded documents
Scopus	WOS	LAR	RRAAE
No exclusion criteria	1874	927	619	853	4273
Documents obtained after applying exclusion criteria	1683	875	510	727	3795	478
Documents after the title reading<= /span>	63	90	16	42	211	3584
Documents after reading the summary and conclusions	44	26	14	35	119	92
Documents after reading the full text	38	21	8	32	99	20

Developed by: The authors

Results and Discussion=

The 99 selected research documents analysis is reported and discussed in two sections: a meta-analysis and descriptive analysis.

Meta-analysis

A 4W analysis (When, Who, what, and where) was developed to better detail the results. The starting point is the "When" field, for which a temporal distribution is used, as detai= led in Figure 1. The number of studies published in the different years analyze= d is observed in this figure.

Notably, 2014 and 2020 reflect the most significant number of research studies carried out, with 15 and 13 studies, respectivel= y. In addition, an increase in publications from 2014 to 2020 can be observed since the average number of published documents is 10.7, with a rise of 6 studies compared to the time interval from 2010 to 2013 (4 documents). Since the data collection period was carried out during 2021, this year is not considered in this analysis to avoid misinterpretation of the results.

Figure 1

Time distribution of sample documents.

Developed by: The authors (based on systematic literature review)

It is pertinent to mention that, at the highest pe= ak of the sample, in 2014, only 33.3 % of the 15 published studies talk about resilience, while the remaining 66.7 % focused on textile sector indicators= and plant layout design indicators. Of the latter, most of the indicators menti= oned in the studies are related to business management, lead times, failures, pr= oductivity, and environment (Azadeh et al., 2014a; Miniguano, 2014). Although in the second peak, corresponding to the year 2020, there is a decrease of two investigations compared to the previo= us year analyzed, the studies on resilience in the industry amounted to 53.84 = %. Despite this, it represents an increase of only two more investigations on resilience in 2014. Regarding the studies on indicators of the textile sect= or and FLP in 2020, the approach is similar to that of 2014. It can be noted t= hat the perspective of the indicators studied in the textile sector for the facility layout design resides in the financial and productive scope. Therefore, these studies emphasize production costs, fulfillment of safety regulations, and environmental factors to a lesser extent (Quispe et al., 2020).

If the documents are analyzed in detail, there is a clear difference in terms of the focus and publication trend of the theses = and articles. Regarding the year of publication of the last ones, figure 2 show= s a clear increasing trend, starting in 2014, with 2020 being the year with the highest number of publications of the articles; presenting 1 study about FL= P, 2 focused on indicators in the textile industry and 7 about resilience. The studies related to the latter topic remain centered on resilience measureme= nt methodologies, resilience factors in the industry, and decision-making for resilient supply chains (Piprani et al., 2020).

Figure 2

Time distribution of sample articles

Developed by: The authors (based on systematic literature review)

The part of the sample corresponding to theses presents only two studies focusing on resilience applied to the industry, published in 2012 and 2017, which represents 5 % (2 studies) of the analyzed theses. In contrast, FLP and indic= ators in the textile industry represent 55 % (22 studies) and 40 % (16 studies) of the total samples of this type of documents. In addition, the years with the highest publication of these topics are: 2014 for FLP and 2015 for studies related to indicators of the textile sector.

As shown in Figure 3, the highest peak of the enti= re thesis sample occurs in 2014, with 2 studies referring to textile industry indicators and 7 to FLP. The common focus of the last mentioned topic resid= es in the application of facility distribution models in which the indicators = are a fundamental part of the study, in addition to compliance with regulations= related to occupational safety, employee comfort and the reduction of production co= sts (De la Cruz, 2014; López, 2014).

Figure 3

Time distribution of sample theses

Developed by: The aut= hors (based on systematic literature r= eview)

Continuing with the 4W analysis, for practical purposes, it is necessary to carry out the "Who" and "What&q= uot; aspect separately in terms of theses and articles. Regarding to the “Who” aspect, the 59 papers in the sample were considered. Figure 4 shows the journals with the highest number of publications, considering the three thematic areas, which include: textile industry indicators, FLP or Resilien= ce.

Figure 4

Articles per journal

Devel= oped by: The authors (base= d on systematic literature review)

With the aforementioned, it is possible to continue with the “What” aspect, i.e., to know what is developed in the studies, as = far as articles are concerned. Obtaining that, of the 59 articles, 6.7 % corres= pond to FLP studies, 16.94 % to textile industry indicators, and 76.36 % to resilience. The four journals with the most publications related to the top= ics of study are the International Journal of Production Research with seven publications, Computers & Industrial Engineering with five publications, and the Journal of Loss Prevention in the Process Industries and the Safety Science with four publications each. In the journals mentioned, the focuses= of the publications, almost entirely, are on resilience, emphasizing the detec= tion of disruptive events (Burnard & Bhamra, 2011), the study of competitive strategies, and the construction of methodological frameworks for business resilience building = (Acquaah et al., 2011).

Similarly, for the " Who" aspect referre= d to the theses, the universities in which the studies were published, and their respective thematic areas are analyzed, thus, it is possible to answer the "What" field. Of the total number of theses analyzed, 22 studies = (55 %) concern FLP, 16 studies (40 %) indicators in the textile field and only 2 studies (5 %) resilience. As for the Technical University of Ambato, which = has the largest number of theses (35% of the theses), the studies mainly deal w= ith FLP and indicators in the textile sector, highlighting the focus of the lat= ter on indicators in the area of production for decision making (Gordon, 2015; Yépez, 2017).

The final step in the 4W analysis analyzes the geographic origin of the sample; thus, the “Where” field is answered. As for the articles, the results indicate that studies have been conducted in 25 countries detailed in figure 5. Furthermore, the findings reveal those four countries with the highest number of publications account for more than 50 = % of the sample, i.e., 31 out of the 59: the USA with eleven, Iran and UK with seven, and India with six. The studies developed in the United States, speak almost entirely about resilience, presenting an increase from the year 2018, such researches present a common approach, which is the measurement and implementation of resilience to face risks, through decision-making models, considering resilient factors. Most studies denote three main characteristi= cs, which are: the assessment of resilience, the association of resilience to a system and the future benefits (MacKenzie & Hu, 2019). Similarly, several studies propose systemic meth= ods to improve risk management and safety through resilience analysis framework= s. As mentioned, the studies analyzed present similarities, since all of them consider technical and social factors as key points to manage an organizati= on, and also establish basic aspects such as: early detection, error tolerant design, plasticity, recoverability and several basic resilience metrics, th= us obtaining key tools for the early detection of risks (Jain et al., 2018). As for the UK and Iran, since 2013 there has bee= n an increase in their publications. The main topic of these studies is resilien= ce with a total of 9 studies together and 3 on FLP in the textile industry. The trend in these countries in terms of resilience is repeated with the United States, as they propose methodologies for improvement, as well as conceptual frameworks for measuring resilience (Mehrjerdi & Shafiee, 2021). The FLP studies propose methodologies for optimization in plant layout design, as well as algorithms for plant select= ion (Vitayasak et al., 2017).

Figure 5

Distribution of sample papers by country

Developed by: The authors (based on systematic literature review)=

Regarding the research corresponding to theses, si= nce a Latin American database (LA Reference) and an Ecuadorian repository (RRAA= E) were used, most of the studies analyzed were developed in countries related= to these sources of information, so that Ecuador predominates with 32 studies, followed by Spain with five studies; thus, 92.5% of the theses sample is represented by the countries mentioned above. Analyzing the Ecuadorian cont= ext in more depth, it is worth mentioning that in the country there are no stud= ies on resilience applied to FLP, but there is a clear tendency to analyze, pro= pose and apply the distribution of facilities, as well as management models base= d on key performance indicators, as shown in figure 6, which shows the thematic areas of the universities in the sample belonging to Ecuador in terms of theses. In addition, as mentioned in the "Who" field referring to theses, the Technical University of Ambato tops the list with the highest number of publications, however, it is notable that the tendency of the country's universities resides only in the two topics shown, leaving resili= ence aside.

Figure 6

Distribution of theses per university

Developed by: The authors (based on systematic literature review)

Descriptive Analysis

This section focuses on answering the three resear= ch questions obtained through the PICO strategy, detailed in the methodology. = The first question corresponds to the variables or indicators to be consider= ed in a resilient industry model. To this end, 46 studies comprised of articles and theses have been analyzed. These studies describe evaluation methods and strategies to identify resilience factors and indicators in the industry. For example, Aleksić et al. (2013) propose a method to assess organizational resilie= nce through a fuzzy mathematical model, proposing internal, external, and resilience factors for subsequent evaluation. This resilient measurement facilitates learning and improvement of various aspects since it is possibl= e to report externally and demonstrate a certain level of performance, efficient= ly controlling and monitoring processes. Therefore, according to the authors, a high resilience potential with minimized costs allows increasing the effectiveness of the processes. In the same manner, Burnard and Bhamra (2011) approach the detection of disruptive events and t= he response actions of an organization. For this, they propose a conceptual framework of resilient organizational response. The factors described facilitate decision-making in the face of problematic and turbulent environmental conditions by adjusting to the immediate risk and preparing f= or future uncertainty. Finally, Pournader et al. (2016) employ a multi-method approach using data envelop= ment analysis models and fuzzy set theory to create an analytical model to assess resilience to supply chain (SC) risks. The information described ensures the identification and appropriate mitigation of SC trouble sources.

It should be emphasized that, for the most part, t= he studies mention that there is no single set of resilience elements and fact= ors in the industry. Conversely, these should be used according to the organization; thus, the quantification of resilience is adequate since they contribute significantly to the competitiveness of SMEs. Therefore, any weakness in the factors would cause inefficient and inadequate use of resources, leading to frustration and waste (Gunasekaran et al., 2011). Nevertheless, through all this research about resilience, it is possible to synthesize the information, obtaining as a result, a set of indicators in which most of the authors agree, as shown in= table 2.

Table 2

Industry resilience indicators and variables

Indicator	Variables
Adaptive capacity	-&= nbsp; Access to information=
-&= nbsp; Communications and relationships
-&= nbsp; Information and knowl= edge
-&= nbsp; Innovation=
-&= nbsp; Leadership=
-&= nbsp; Decentralized decision making
Planning	-&= nbsp; Planning strategies
-&= nbsp; Proactive posture
-&= nbsp; Recovery priorities
-&= nbsp; External resources
Key vulnerability management	-&= nbsp; Severity of occupatio= nal accidents
-&= nbsp; Frequency of occupati= onal accidents
-&= nbsp; Participation in dril= ls
-&= nbsp; Process safety
-&= nbsp; Unplanned shutdowns p= er year
-&= nbsp; Accident learning

Table 2

Industry resilience indicators and variables (continuación)

Indicator	= Variables
Just culture	-&= nbsp; Understanding and perception of errors
-&= nbsp; Awareness<= /span>
-&= nbsp; Fault tolerances=
Information flow efficiency=	-&= nbsp; Management communicat= ion
-&= nbsp; Control capacity=
Managerial Efficiency/ Top Management Commitm= ent	-&= nbsp; Rules and procedures<= o:p>
-&= nbsp; Violations of regulat= ions
-&= nbsp; Work pressure and str= ess
-&= nbsp; Self-organization
-&= nbsp; Information culture
-&= nbsp; Teamwork
System safety efficiency	-&= nbsp; Safety Policies<= /o:p>
-&= nbsp; Safety equipment=
-&= nbsp; Safety and physical problems

Developed by: The authors (based on systematic literature review)

To answer the second research question, which corresponds to: What indicators are used in the textile industry? It= is necessary to know the different perspectives of the indicators to have a cl= ear understanding of the trend in the industrial sector under study. In most investigations, indicators are applied or analyzed in the production and management areas since they are of interest to know the state of the main operations of the companies. The importance of indicators lies in the ease = of obtaining a global vision of the company and, thus, knowing the most critic= al parameters and the causes of the existing problems, for example, Montava et= al. (2010), propose a series of indicators for management in= the textile industry from different perspectives.

The authors highlight financial, quality, and innovation perspectives, presenting indicators that consider the consequenc= es of business management strategies and critical success factors, to a lesser extent, the indicators related to the environment focus their attention on water consumption, global warming, or resource use. As the study developed = by Reyes et al. (2020), in which a method for selecting life cycle assessment indicators in the textile industry in France is presented. This method is adapted as an environmental learning engine since the approach mentioned is one of the most difficult to implement in the textile sector d= ue to the nature of its processes. Therefore, the importance of this type of indicator lies in calculating the environmental impact of various textile products.

Most of the indicators analyzed refer to the activities of the production area or top management administration, conside= ring factors such as quality or the environment. However, the supply chain and logistic indicators are left aside in most cases. Table 3 summarizes the indicators and variables obtained through synthesizing the studies compiled= about the textile industry.

Table 3

Textile industry indicators and variables

Perspecti= ve	Indicator=	Variable<= o:p>
Financial=	<= span style=3D'mso-list:Ignore'>-&= nbsp; Financial position	<= span style=3D'mso-list:Ignore'>-&= nbsp; Liquidity<= /span>
<= span style=3D'mso-list:Ignore'>-&= nbsp; Solvency
<= span style=3D'mso-list:Ignore'>-&= nbsp; Cash flow<= /span>
<= span style=3D'mso-list:Ignore'>-&= nbsp; Operating efficiency ratios	<= span style=3D'mso-list:Ignore'>-&= nbsp; Inventory turnover
<= span style=3D'mso-list:Ignore'>-&= nbsp; Profitability ratios<= o:p>	<= span style=3D'mso-list:Ignore'>-&= nbsp; Gross margin percenta= ge
Commercia= l	<= span style=3D'mso-list:Ignore'>-&= nbsp; Customer indicators	<= span style=3D'mso-list:Ignore'>-&= nbsp; Distribution costs
<= span style=3D'mso-list:Ignore'>-&= nbsp; Billing
<= span style=3D'mso-list:Ignore'>-&= nbsp; Non-payments
<= span style=3D'mso-list:Ignore'>-&= nbsp; Commercial network	<= span style=3D'mso-list:Ignore'>-&= nbsp; Achievement of budget= ed sales
Human resources	<= span style=3D'mso-list:Ignore'>-&= nbsp; Staff satisfaction	<= span style=3D'mso-list:Ignore'>-&= nbsp; Absenteeism
<= span style=3D'mso-list:Ignore'>-&= nbsp; Occupational accident= s
<= span style=3D'mso-list:Ignore'>-&= nbsp; Occupational accident costs
Innovatio= n	<= span style=3D'mso-list:Ignore'>-&= nbsp; Innovation indicators=	<= span style=3D'mso-list:Ignore'>-&= nbsp; New article benefits<= o:p>
<= span style=3D'mso-list:Ignore'>-&= nbsp; Innovation efficiency=
<= span style=3D'mso-list:Ignore'>-&= nbsp; R&D&I project= s
Production systems	<= span style=3D'mso-list:Ignore'>-&= nbsp; Quality and service of the manufactured product	<= span style=3D'mso-list:Ignore'>-&= nbsp; Cost of non-quality
<= span style=3D'mso-list:Ignore'>-&= nbsp; Returns
<= span style=3D'mso-list:Ignore'>-&= nbsp; Failed delivery deadl= ines
<= span style=3D'mso-list:Ignore'>-&= nbsp; Percentage of defects= and waste
<= span style=3D'mso-list:Ignore'>-&= nbsp; Ordering services
<= span style=3D'mso-list:Ignore'>-&= nbsp; Environmental efficie= ncy	<= span style=3D'mso-list:Ignore'>-&= nbsp; Cleaner production knowledge
<= span style=3D'mso-list:Ignore'>-&= nbsp; Compliance with environmental standards
	<= span style=3D'mso-list:Ignore'>-&= nbsp; Resource management
<= span style=3D'mso-list:Ignore'>-&= nbsp; Solid waste managemen= t
<= span style=3D'mso-list:Ignore'>-&= nbsp; Time	<= span style=3D'mso-list:Ignore'>-&= nbsp; Lead time for customer service
<= span style=3D'mso-list:Ignore'>-&= nbsp; Lead time for incoming orders
<= span style=3D'mso-list:Ignore'>-&= nbsp; Supplier response tim= e
<= span style=3D'mso-list:Ignore'>-&= nbsp; Average transit time<= o:p>
<= span style=3D'mso-list:Ignore'>-&= nbsp; Operational times

Developed by: The authors (based on systematic literature review)

Completing the descriptive analysis, the present s= tudy answers the third research question, which refers to “What are the varia= bles or indicators that can be used in a plant layout design in MSMEs in the tex= tile sector with a resilient approach?” Initially, through the analysis of t= he 99 studies compiled, it can be said that no research has been found in which these two areas interact. Thus, the benefits of resilience in plant layout design have not yet been thoroughly studied. This means that information is= not yet at the fingertips of organizations. However, the constant need to adapt= to new, highly competitive markets generates circumstances in which companies = must effectively know the current situation of their processes, operations, and = performance in general. In this manner, MSMEs can understand the areas and variables generating problems, and thus their responses are quick and appropriate.

Most of the FLP studies in the textile sector incl= ude indicators that consider elements such as the materials flow, transport tim= e, travel distances, or the use of machines. As Quispe et al. (2020) mention, these indicators are related to the low production efficiency since they cause unproductive times and unexpected production stops. Nonetheless, these criteria are not the only ones to cons= ider since other indicators are important to ensure optimal plant layout design = and monitoring. For instance, Azadeh et al. (2015) propose a multivariate fuzzy approach to find the appropriate strategy for the distribution of facilities with ambiguity. In addition, the authors use operational, qualitative, and dependent indicators such as distance, adjacency, and shape ratio (Lin & Sharp, 1999). In this manner, the efficiency and accuracy of t= he models are greater, obtaining a correct arrangement of the work areas and machinery, thus achieving an economic reduction and at the same time a safer and fairer distribution for employees (Vitayasak et al., 2017).

It is necessary to propose a series of indicators = for the plant layout design to have a resilient approach and respond to the FLP principles. For this, seven factors synthesize the information present in a facility layout design. These factors are material, equipment, waiting, services, facilities, change, and finally, the human element (Quispe et al., 2020). The indicators are detailed in table 4.

Table 4

Proposed indicators and variables for resilient plant layout design

Table 4

Proposed indicators and variables for resilient plant layout design (continuación)

Factor	Indicator	Variable<= /span>
Service	<= span style=3D'mso-list:Ignore'>-&= nbsp; System safety efficie= ncy	<= span style=3D'mso-list:Ignore'>-&= nbsp; Emergency equipment design
<= span style=3D'mso-list:Ignore'>-&= nbsp; Safety routes
<= span style=3D'mso-list:Ignore'>-&= nbsp; Safety and physical problems
Building/= Facilities	<= span style=3D'mso-list:Ignore'>-&= nbsp; Adjacency<= /span>	<= span style=3D'mso-list:Ignore'>-&= nbsp; Index of proximity between activities
<= span style=3D'mso-list:Ignore'>-&= nbsp; Perimeter of contact between activities
<= span style=3D'mso-list:Ignore'>-&= nbsp; Space sufficiency and utilization	<= span style=3D'mso-list:Ignore'>-&= nbsp; Space utilization efficiency
<= span style=3D'mso-list:Ignore'>-&= nbsp; Productive area utilization
Change	<= span style=3D'mso-list:Ignore'>-&= nbsp; Facilities layout flexibility	<= span style=3D'mso-list:Ignore'>-&= nbsp; Expansion flexibility=
<= span style=3D'mso-list:Ignore'>-&= nbsp; Volume flexibility
<= span style=3D'mso-list:Ignore'>-&= nbsp; Building expansion	<= span style=3D'mso-list:Ignore'>-&= nbsp; Available outdoor are= a
<= span style=3D'mso-list:Ignore'>-&= nbsp; Current area
Human Resource	<= span style=3D'mso-list:Ignore'>-&= nbsp; Staff satisfaction	<= span style=3D'mso-list:Ignore'>-&= nbsp; Absenteeism
<= span style=3D'mso-list:Ignore'>-&= nbsp; Occupational accident= s
<= span style=3D'mso-list:Ignore'>-&= nbsp; Training and developm= ent	<= span style=3D'mso-list:Ignore'>-&= nbsp; Cost of training prov= ided
<= span style=3D'mso-list:Ignore'>-&= nbsp; Operators with degree= s or specific training
<= span style=3D'mso-list:Ignore'>-&= nbsp; Fair culture	<= span style=3D'mso-list:Ignore'>-&= nbsp; Understanding and perception of errors

Developed by: The authors (based on systematic literature review)

Conclusions

· Through the literature review, 99 research studies were identified, of which 59 articles and 40 theses were analyzed systematically, reproducible, and critically. The most common indicators and variables in terms of business resilience, FLP, and the text= ile industry were determined from the information obtained.

· The analysis of studies about resilience, indicators in the textile industry, and FLP in the textile indu= stry denotes a rising trend in research development on the topics mentioned abov= e. Indeed, in the period 2015-2021, there was a rate of published research of 9.71, higher than the period between 2010 and 2014, which was 6.2. In both periods, research on this topic focused on resilience measurement methodologies, resilience factors in the industry, and decision-making predominated.

· Resilience research is superior to the other two topics analyzed in the study as it represents 46.46 % of the total sample of 99 research studies. In the Ecuadorian context, it is notab= le that resilience has been poorly explored, since the studies that passed the methodological and exclusion criteria only refer to FLP and indicators in t= he textile industry. In the international context, studies on the subject in question focus almost entirely on the evaluation and classification of resilience factors in the industry; no study has analyzed the interaction between FLP and resilience. Furthe= rmore, several authors emphasize that the use of indicators other than those traditionally used in the design of facilities could allow a better integra= tion of resilience in organizations.

· As for the studies related to indicators in the textile industry, most of them consider aspects such as commercial, material or financial, however, several key elements such as la= bor or resilience are left aside. In addition, the indicators analyzed apply ma= inly to the production area and top management. Regarding FLP in the textile industry evidenced the use of indicators that evaluate the material flow, transit times, distance traveled, machine utilization, or the geometry of t= he building. Finally, a series of indicators have been proposed for the facili= ty layout design, considering a resilient approach. These indicators respond to the FLP principles based on seven main factors: material, machinery, waitin= g, service, facilities, change, and human resources.

·&nb= sp; Despite certain limitations of th= is type of research, it is expected that the work will serve as a key tool for future studies in which the interaction between FLP and resilience is studi= ed. For instance, one of the research limitations lies in obtaining the sample since it depends on the search terms and the database used. The subjectivit= y of the study is another limitation. The approach of the indicators for the pla= nt layout design with a resilient attitude depends mainly on judgment, experie= nce, and the number of researchers involved. Nevertheless, the systematic litera= ture review provides a broad overview of the current trends of the aspects analy= zed despite these issues.

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