Quality control of the jute bag production process

The present work was developed in the Texoro Textile Industry of Bayamo, Granma, Cuba (Sakenaf), belonging to the Light Industry.

The object of study was quality management.

This research pursues the fundamental objective of designing a quality control procedure to improve the production process in the Light Industry, in order to contribute to the efficient use of resources, also promoting corporate image and economic efficiency. It was based on the use of the materialistic dialectical method, empirical methods, statistical tools: descriptive statistics, control charts and process capacity, applying the Minitab16 statistical package. In addition, the methodological procedures for the application of statistical process control as an instrument to control quality and the creation of a Failure Analysis and Effects Model (FMEA), based on the elaboration of causes and / or problems, are presented.The work ends with the conclusions and recommendations proposed by the author. The consulted bibliography is also included.

Key words: Quality management, control, resources, improvement.

Introduction

In the search to improve the competitiveness of an organization, which is important and key in the processes, as well as the results that we want to improve, it is necessary to measure them (Humberto Gutiérrez Pulido, Statistical Quality Control and Six Sigma, 2007). The following sentence summarizes what is communicated in this section: tell me what you measure and how you analyze it, and I will tell you what is important for your area and for your industry or for your company. Or in the words of HJHarrington: ¨Measuring is understanding, understanding is obtaining knowledge, having knowledge is having power. From the beginning of its existence, the peculiarity that differentiates human beings from other living beings is their ability to observe, measure, analyze and use information to generate change ”(Harrington, 1997).

Business management must be able to achieve a chain reaction by applying the 8 basic principles of quality management and the optimal integration of its strategic processes, its key processes and its support processes, on the one hand the true meaning of quality, as it is perceived by consumers, and on the other the energies are concentrated in exposing and overcoming the enormous waste that afflicts conventional companies, all this is summarized within the process map already previously implicitly addressed, which synthesizes the client's requirements at the entrance of said map and on the other hand the exit of the new product with a certain added value that will be perceived by the client.

In the present procedure that the author proposes, in addition to maintaining control over the production process, he himself emphasizes the efficient use of resources, since this good use will generate greater profit margins for the industry, this is indicated o It will be achieved through reducing the tolerance of the technical specification of the product, pointing out that this reduction in tolerance should not affect the specification indicated by the client, but rather should be carried out from the internal point of view of the industry within the framework allowable specification detailed by external customer.

Thus, it is necessary to implement a quality control procedure that contributes to the efficient use of inputs, while influencing the reduction of quality costs, since up to now in reports presented by quality specialists In the boards of directors, it is observed that this industry only applies actions associated with technical inspections to the process area, through the standards of each assortment, that is, consumption standards and, finally, the procedure manuals of the internal control system in its five components and the complementary ones that pay to the system as it is the case of the warehouses and other fundamental activities not being sufficient to achieve the efficient use of the productive inputs, to focus on the vital facts,nor do they allow the analysis of all the data from the key production guides, in order to identify the sources of variability, analyze their stability and forecast their performance, and they do not allow the rapid, timely and low-cost detection of process abnormalities. taking into account all these elements and the transformations that are currently taking place, it is considered appropriate to implement tools that allow perfecting resource planning and minimizing the costs of quality and the efficient use of productive inputs, while affecting the reduction of quality costs and rational use of the economic task / resource category.analyze their stability and forecast their performance, in addition to not allowing to detect abnormalities in the processes quickly, opportunely and at low cost. Taking into account all these elements and the transformations that are currently taking place, it is considered appropriate to implement tools that allow perfecting resource planning and minimizing the costs of quality and the efficient use of productive inputs, while influencing the reduction of quality costs and making rational use of the economic task / resource category.analyze their stability and forecast their performance, in addition to not allowing to detect abnormalities in the processes quickly, opportunely and at low cost. Taking into account all these elements and the transformations that are currently taking place, it is considered appropriate to implement tools that allow perfecting resource planning and minimizing the costs of quality and the efficient use of productive inputs, while influencing the reduction of quality costs and making rational use of the economic task / resource category.Taking into account all these elements and the transformations that are currently taking place, it is considered appropriate to implement tools that allow perfecting resource planning and minimizing the costs of quality and the efficient use of productive inputs, while affecting the decrease of quality costs and rational use of the economic category task / resource.Taking into account all these elements and the transformations that are currently taking place, it is considered appropriate to implement tools that allow perfecting resource planning and minimizing the costs of quality and the efficient use of productive inputs, while affecting the decrease of quality costs and rational use of the economic category task / resource.

Based on the foregoing, it is declared as a general objective to design a quality control procedure to improve the jute bag production process (KHA-417-999).

And as a hypothesis of relationship between two variables, it is proposed that if the quality control procedure of the jute bag production process is designed, taking into account techniques and methods of statistical control, in accordance with the process approach in the management of quality, there will be a tool that contributes to eliminating the insufficiencies detected in the Bayamo Texoro Base Business Unit.

Development

Quality control procedure in the jute bag production process (KHA-417-999) at UEB Texoro Bayamo, Granma.

The main objective of this development is to present the exhaustive description of the procedure proposed by the author for quality control in the Light Industry. Firstly, it should be noted that the methodology provided covers how to diagnose, control and monitor the production process and finally propose a continuous improvement strategy once the causes assigned to the production process have been detected from a series of techniques and tools contained in the statistical process control and the application of a Failure Mode and Effects Analysis (FMEA).

The procedure consists of 4 phases which will be accompanied by different steps necessary to carry them out, they also carry with them the objective of each phase and the identification of each one, in addition a schematic representation of the procedure is presented.

For the application of the procedure it is necessary the constitution of a working group to carry out all the analyzes and evaluations of the conjunctures that will appear during the results that are obtained and thus focus on the vital points to achieve a better use of the inputs productive. Its constitution is necessary in the conditions of the Cuban industry because few, for not being absolute saying that none, have a statistical intelligence system as is the case in the present investigation that is based fundamentally on the statistical-mathematical method that will allow permanently monitor and assess process events and a reliable internal data system that accesses accurate and reliable assessments on which to base decision-making processes.The author considers that in the Cuban industrial system there is not the necessary number of people who can be considered as experts in this subject, since currently conventional industries still do not carry out their operations through systematic statistical control, since the systems and methods Production valid until the early 1970s have lost responsiveness to the profound changes that have occurred worldwide. To survive and succeed in the present century, industries will have to put into practice new philosophies and methods as already mentioned above. Great efforts will be required to overcome organizational inertias, and those responsible for the changes will need a strong level of leadership.The procedure establishes that the working group is made up of specialists.

In the process of selecting the members, and forming the working group, the following moments must be observed:

Engage the work team and inform the other members of the entire industry as a whole about the importance of the subject in the search for continuous improvement and thus achieve the commitment of all staff with the organization. Consider the level of education, the position held in the industry, years of experience, and theoretical knowledge of the subject. The interview is used as a tool. To obtain the collaboration of the members of the work group creating the necessary conditions for the development of their work and to explain the importance of the task such as obtaining their collaboration commitment. Explain to the members of the group the objectives of its creation and the methods to be followed during the work sessions, as well as explaining the general objective sought in the research.train group members about the main characteristics and ways of interpreting results from the application of the mathematical statistical method.

Finally, for the creation of this work team, it is necessary to carry out a survey which details the fundamental questions that make it possible to substantiate the level of competence. This result must be validated through data processing using the criterion of competence coefficient, or by other criteria and also through the use of computer software.

Quality control procedure for jute bag (KHA-417-999)

Phase 1. Preparation of inputs, analysis, identification and description of the process

This phase has as a fundamental objective the identification and description of the production process, as well as the selection of the variables to be controlled, in addition all those activities that take place in the production process that contribute to the quality of the final product must be identified, for what must be taken into account the norms and specifications established to define the characteristics of the production and what will be those activities that will be developed to guarantee the production process and that contribute to the quality of the product.

Step 1. Preparation of supplies

Objective:Identify the inputs with which the product is manufactured, as well as the quality standards of said inputs for a better obtaining of the finished product and at the same time reducing future costs of quality through the good preparation of the material. premium to use. In order to carry out this stage, it is necessary that the work team first request the technical sheets that refer to the inputs with which the product is made, in addition to checking the compliance with the quality standards of these inputs contained in the certified standards in force in the industry and also through the observation method, compliance with the temperatures to which they must be subjected, as well as the humidity in the quality laboratory in the Industry, if it exists.

Step 2. Identification and description of the process

Objective: Describe the technological components and the process flowchart.

The information to be collected in this step will be carried out from the identification of the production process, taking into account the technological components and all the production threads that make up the manufacture of the product. In this first step it is necessary to resort directly to the production process, consulting or creating the production flow if it does not exist, since it will obtain a vision of the real characteristics that the industry has in terms of its technology park that allows production. The author points out that all sub-processes must be delimited. For the creation of the flowchart specialized bibliographies must be used, where the legend to follow of the flowchart is evident, for this it is recommended to use OTIDA.

Step 3. Technological analysis of the process

Objective: To analyze the technological component of the production process once identified, in order to determine if these components are in full condition for the efficient achievement of production in terms of meeting the quality characteristics of the final product.

Once the process identification and description has been carried out, the analysis of the technological components and their characteristics is carried out, since it will allow having a clear vision of the level of production and compliance with the quality requirements of the finished product.. In addition, knowing the degree of depreciation, as well as the level of feasibility of the equipment, which will provide quantification of the technical condition of the equipment. The information of the manufacturer of these technological components must also be requested, that is, to know the initial theoretical capacity and the degree of annual depreciation. For this analysis, the observation method and the revision of the theoretical manufacturing standards of the machinery used in the entity are used.

Phase 2: Selection and description of the variable

This phase has the fundamental objective of identifying the variables to be controlled, as well as detailing the product specifications according to the required quality standards. Once the technological analysis of the equipment has been carried out, the variable that is estimated to be controlled corresponds to its degree of importance and that has an impact on the achievement of a certain objective, this selected variable can be with respect to length, weight, thickness, and other attributes.

Step 1. Set the variable to control

Objective:Constitute the variables object of study to be developed in the research, as well as the description of its relevance in terms of economic efficiency within the production process that gives rise to the importance of studying it and its behavior of incidence in the final product and the need for control. For the selection of this variable, a survey will be carried out that refers to the delimitation of the quality variable to be controlled with respect to the remaining quality variables present in the product. This survey should be applied to a representative sample of different strata of the entity's staff, made up of administrative, marketing, quality management and executive staff.For the processing of said survey, Kendall's agreement criteria will be used from the SSPS Manager software.

Step 2. Product specifications

Objective: Consult the quality characteristics present in the indications and specifications that the final product must contain, regarding the selected quality variables. Here an analysis of the characteristics that the finished product must contain, that is to say have a description of the quality attributes focused mainly on the one or those attributes that you want to control. These specifications must be requested from the quality management department from the product's technical sheet.

Step 3. Data collection and conformation

Objective: Create the database with which the analysis of the variable in question will be carried out once the characteristics and quality specifications have been identified. This is done by consulting the database that allows obtaining such information, that is, in economic records or characterization carried out by quality specialists in the Industry, in addition an assessment must be made between one and other data criteria contained in certain periods of time.The author clarifies that here some criteria from different authors must be taken into account in terms of obtaining the sample in terms of quality management and a historical-logical analysis of the behavior of the children must also be carried out. primary data to establish a comparison of the fluctuations of the process regarding the variable in question. Regarding obtaining the desired sample, the simple random sampling contained in Humberto Gutiérrez Pulido, 2007 must also be taken into account. The author also points out that a 95% confidence level must be carried out regarding the processing of the data since it is the most commonly used value. These obtained data must be reflected in a table based on the own elaboration related to the entity.

Step 4: Descriptive and comparative analysis of primary data

Objective:Carry out a primary analysis of the data of the variables under study in order to obtain a first idea of its performance in the process and specifically of the measurement process, and the possibility of registry errors, systematic error among other difficulties that characterize the process. Here an exhaustive work must be carried out with the work team since this will allow the comparison of the data between one period and another, which will lead to having a vision of the variations that exist between the results obtained in correspondence with the task category. /resource. This is also important to do as this is where the need to control the quality variable chosen will be demonstrated as a result of the analyzes carried out in order to obtain the optimal results,also to contribute to the efficient use of inputs after the application of quality control tools for the quality variable that allows better export volumes. To carry out the passage, it is necessary to use the Minitab 16. software, which will make the statistical description and other descriptive elements possible. For the descriptive analysis of the data, the Anderson-Darling criterion is taken into account to verify that the data follow a normal distribution.that will make possible the statistical description and other descriptive elements. For the descriptive analysis of the data, the Anderson-Darling criterion is taken into account to verify that the data follow a normal distribution.that will make possible the statistical description and other descriptive elements. For the descriptive analysis of the data, the Anderson-Darling criterion is taken into account to verify that the data follow a normal distribution.

Phase 3. Status of the process

Objective: To analyze in detail the stability and capacity of the process and determine if said process is capable and if the level of non-conformities is low enough to guarantee that there will be no immediate efforts to try to lower them and thus improve their capacity. For this stability study, the calculation of the stability index must be taken into account, it can be obtained from obtaining the EWMA and CUSUM control charts. In this phase, the mathematical statistical method will be used, as well as some computer software. For this research, Minitab 16 will be applied.

Step 1: Delimit historical data

Objective:To determine in which state the process falls, for this it is necessary to resort to historical data and analyze them for the different output variables of the process or subprocess under analysis, these data were identified in step 4 of phase 2. To determine in which state the process it is necessary to resort to this historical data and analyze it for the different output variables of the process or sub-process under analysis. Historical data is understood to be those that reflect the reality of the process during a considerable period of time in which the process has not undergone major modifications (Gutiérrez, 2007). It is not just about having enough data, but also results from a period of time in which no major changes or modifications have been made to the process,which should not be a major problem in established processes.

Step 2: Analyze stability

Objective: To standardize the manufacturing conditions to evaluate the stability of the processes, mainly the verification of the normality assumptions, by using the predicted analysis graphs and the calculation of the St index, as well as the analysis of the control charts seeking identify special patterns of variation, that is, points outside the limits. To study the stability of the process over time that includes the historical data and calculate the St index, here the author proposes to proceed as follows; make an initial study with the historical data, that is to say analyze all the data in the same control chart and thus seek to identify the special patterns of variation and based on this draw conclusions and calculate the instability index.

Step 3: Determination and interpretation of process capacity

Objective: Apply a capacity analysis, using the different tools such as obtaining the Cpk, Cp and histogram indices and interpreting it. In order to identify if there are capacity problems and identify if it is due to centering problems, or excess variation and, in general, how the data is distributed with respect to specifications. The author indicates that a capacity analysis should be carried out on the historical data, which will allow identifying if the capacity problem is due to centering problems, excess variation and, in general, see how the data is distributed with respect to the specifications, with which can lead to some guesswork about the causes of low capacity if that was the reason.Like the previous steps to obtain the process capacity, the use and application of the mathematical statistical method is necessary, through the use of the Minitab 16 software. In addition, the states of a process should be consulted in Gutiérrez, 2007, in order to this way to be able to frame the process in question.

Phase 4.Create the Failure Mode and Effect Analysis (AMEF)

Objective: The main objective of this phase is to apply the tools that will allow detecting the critical aspects that require attention that cause the variability and the not possible efficient use of the inputs, and once the diagnosis of the state of the process has been carried out, to from the studies carried out on the selected quality variable and based on the results obtained. The AMEF is a tool that was originally aimed at detecting failures during the design or redesign of the product and failures in the production process (FMEA, 1995). In recent years the scope of the AMEF has been expanded (Lore, 1998; Vandenbrade, 1998; Cotnareanu, 1999).This methodology provides the guidance and steps that a group of people should follow to identify and evaluate potential failures,This AMEF activity has become an almost obligatory activity to guarantee that the products are reliable and improve the efficiency of processes.

Step 1: Identify potential failure modes

This stage will be applied in order to identify the potential failures of the process, together with the effect they cause. From here on, the working group will establish priorities and decide on actions to try to eliminate or reduce the possibility of potential failures that most violate the reliability of the product or the process, and once they have been delimited from each other.

For the identification of potential failures, the interview method will be applied, this interview should be carried out to the personnel in charge of carrying out the recording of errors and abnormalities detected in the process, these personnel should preferably be those personnel who work in the inspection lines or the personnel in charge of the quality control of the process, in addition the consultation of the existing documentation that collects the incidents for each work shift must be carried out, as well as the application of the observation method.

Step 2: Identify the effect and estimate the severity of each failure

Here you should write down all potential failure modes, define the failure mode effects and estimate the severity of the listed effects. The severity of the potential failure effects will be evaluated on a scale of 1 to 10 and will represent the severity of the failure for subsequent operation once this failure has occurred (Annex 1). The severity only refers to or applies to the effect. To define these effects, the work team must rely on the consultation of the criteria and the score for the severity of the effect of the failure in Gutiérrez Pulido, 2007.

For each potential failure diagnosed, the following steps must be performed:

Finding the potential causes of failure and estimating the occurrence of failure due to each cause, this level of occurrence will be estimated on a scale of 1 to 10 (Annex 2).Here the personnel in charge should ask the question: How often is such a failure mechanism activated? The probability of detection must also be estimated, but for this it is necessary to make a list of the current controls of the process and in the event that they do not exist, propose them to the entity, these controls should be aimed primarily at preventing the occurrence of the cause-mechanism of the failure or controls that reduce the failure rate, secondly controls to detect the occurrence of the cause-mechanism of the failure, in such a way that it allows generating corrective actions and finally thirdly from controls that detect the occurrence of the resulting failure mode. This detection should be carried out on a scale of 1 to 10 (Annex 3), specifying that this detection must be focused on these previously described controls. Here, too, the work team must rely fundamentally on the criteria for rating the probability of occurrence of potential causes of failure and on the criterion for estimating the probability of detection in Gutiérrez Pulido, 2007, respectively. Calculate the Priority Risk Number (NPR), which results from multiplying the severity by the occurrence by the detection. In other words, for each effect there are several causes and for each cause a group of controls. The NPR falls in a range from 1 to 1000 and provides a relative indicator of all causes of failure (Gutiérrez Pulido, 2007). The highest numbers of NPR should be given priority for corrective actions,either to prevent the cause or at least to employ better screening controls. Special attention should be given when high NPRs greater than 80 are obtained with high severities. Establish priorities according to the NPR, and for the highest NPRs decide actions to decrease severity and / or occurrence, or in the worst case, improve detection. The entire process followed or studied must be documented in an FMEA format. Review and establish the results obtained, which includes specifying the actions taken and recalculating the NPR. This indicates that it falls into a feedback process.or in the worst case, improve detection. The entire process followed or studied must be documented in an FMEA format. Review and establish the results obtained, which includes specifying the actions taken and recalculating the NPR. This indicates that it falls into a feedback process.or in the worst case, improve detection. The entire process followed or studied must be documented in an FMEA format. Review and establish the results obtained, which includes specifying the actions taken and recalculating the NPR. This indicates that it falls into a feedback process.

The procedure developed in the framework of this research will contribute to better quality management and control in terms of production processes, demonstrating a methodological solution to the scientific problem posed, since it will allow us to have a real vision of the behavior of the quality variable, thus such as the visualization of the behavior of the quality specifications that contribute to a better efficiency of the production process and a better economic profitability of the entity by diagnosing the non-efficient use of production inputs and also making it possible to orient towards the identification of causes or failures whether they are assignable or common, which allow the resources available to be boosted in order to achieve high levels of production based on continuous improvement.

The author then makes a schematic representation of the procedure proposed in Figure 1.

Figure 1. Schematic representation of the procedure

Procedure to improve the management and control of production processes

Procedure to improve the management and control of production processes

Source: own elaboration, adaptation of (Lore, 1998; Vandenbrade, 1998; Cotnareanu, 1999)

Legend:

Legend of Procedure to improve the management and control of production processes

Conclusions

The quality control procedure in the jute bag production makes it possible to maintain constant production monitoring.

This procedure demonstrates that it is feasible for the producing entities to apply statistical process control to achieve higher quality productions and constant monitoring of production. From the application of an AMFE, the possible causes that negatively affect the production will be identified. stability index and focus the process towards the target value.

recommendations

Ensure that the personnel responsible for quality receive the necessary training to carry out the new tasks. Promote the material, technological and human capital conditions of the organization in order to strategically plan the resources aimed at satisfying the needs of customers and better results obtained. Carry out the control and evaluation of the procedure designed to detect and eliminate potential failure modes.

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Annex # 1 Criteria and scores for the severity of the failure effect.

Criteria and scores for the severity of the failure effect.

Annex # 2 Criteria for rating the probability of occurrence.

Probability of occurrence of the cause causing the failure.	Failure rate	Punctuation
Very high: Persistent failures	≥ 100 per thousand pieces 50 for every thousand pieces	10 9
Tall: Frequent failures.	20 for every thousand pieces 10 for every thousand pieces	8 7
Moderate: Occasional failures	5 for every thousand pieces 2 for every thousand pieces 1 for every thousand pieces	6 5 4
Low: Relatively few failures	0.5 per thousand pieces 0.1 per thousand pieces	3 two
Remote: failure is unlikely	0.01 per thousand pieces	one

Source: Gutiérrez Pulido, 2007.

Annex # 3. Criteria to estimate the probability of detection of failure modes.

Criteria	Detection	Inspection types ABC	Suggested range of detection methods	Qualification
Almost impossible	Absolute certainty of non-detection	x	It cannot be detected or cannot be verified.	10
Very remote	Controls probably won't detect it	x	Control is achieved only with indirect or random verification.	9
Remote	Controls have little chance of detection	x	Control is achieved only with visual inspection.	8
Very low	Controls have a low probability of detection.	x	Control is achieved only with double visual inspection.	7
Low	Controls can detect it.	xx	Control is achieved with graphical methods such as CEP (statistical process control).	6
Moderate	Controls can detect it.	x	Control is based on the measurement of variables after the part has left the station or on Pass / Fail type meters that measure 100% of the parts after the parts have left the station.	5
Moderately-high mind.	Controls have a good chance of detecting it	xx	Detection of error in subsequent operations or measurements made in commissioning or first part inspection (for starting causes only)	4

Annex # 3. Criteria to estimate the probability of detection of failure modes. Continuation.

high	Controls have a good chance of detecting it	xx	Detection of the error in the station or in subsequent operations of multiple acceptance steps. You cannot accept dissenting parts.	3
Very high	Controls will almost certainly detect it.	xx	Detection of error in the station (automatic measurement with automatic stop device). Disagreeing parts do not pass.	two
Almost sure.	Controls will surely detect it.	x	Disagreeing parts cannot be made because the point has error prevention from the product and process design.	one