Work methodology and identification of
uncertainties in quality assurance
A case study of internal component manufacturing
in the automotive industry
Richard Michelsson
Martin Wennberg
Master of Science Thesis MMK 2012:x MKN yyy KTH Production Engineering
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Sammanfattning
Idag förekommer inom Scania, liksom fordonsindustrin, ett ökande krav på att uppnå bättre kvalitet (AIAG, 2013). Kvalitetssäkringen sker främst genom att följa den definierade tekniska specifikat-ionen ISO/TS 16949, där Production Part Approval Process (PPAP) utgör en del av kvalitetssäk-ringen. PPAP är en internationellt etablerad kvalitetssäkringsprocess för underleverantörers tillverk-ning. Denna process används även internt på Scania för att kvalitetssäkra introduktionen av nya pro-dukter och tillverkningsmetoder. Att följa PPAP innebär ett relativt omfattande dokumentationsar-bete. Vid hemmatillverkning används i nuläget ett flertal system för att hantera information om bland annat maskiner, artiklar, mätresultat och avvikelser. Dokument skapas och arkiveras idag till stor del i en Windowsbaserad miljö där sökning och uppdatering av information visat sig bli både tidsödande och osäker. Scanias produktionsenheter behöver därför en utvecklad arbetsmetodik för att effektivi-sera dokumenthanteringen i samband med PPAP arbetet.
Målet med detta examensarbete är att identifiera potentiella osäkerheter som kan ha en påverkan på kvalitetssäkringen inom fordonsindustrin. Examensarbetet syftar även till att utforma en utvecklad arbetsmetodik för Scania CV’s dokumenthantering vid genomförandet av PPAP för att säkra kvalitén av hemmatillverkade artiklar vid Scania.
Resultatet har utformats genom en fallstudie av de arbetsprocesser som används inom den interna produktionen vid Scanias motortillverkning. Informationen har insamlats genom kvalitativa inter-vjuer med anställda inom olika avdelningar vid motortillverkningen och genom observationer i pro-duktionen. Informationen om Scanias processer har sedan analyserats och jämförts med litteraturen. Examensarbetet resulterade i ett förslag på en förbättrad arbetsmetodik i form av ett flödesschema för att illustrera hur processberedarna vid motortillverkningen (DM) bör arbeta för att öka den interna kvalitetssäkringen av hemmatillverkade produkter. Potentiella osäkerheter identifierades inom områ-dena: Människa, metod och mätning, där standardiserat arbete ansetts vara det mest kritiska osäker-hetsbidraget vid kvalitetssäkringen.
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Abstract
Currently at Scania, as well as the automotive industry, an increasing requirement to achieve better quality occurs (AIAG, 2013). The quality assurance is primarily done by complying with the defined technical specification ISO / TS 16949, where the Production Part Approval Process (PPAP) form a part of the quality assurance. PPAP is an internationally established quality assurance process for subcontractor manufacturing. This process is also used internally at Scania for ensuring the quality of the introduction of new products and manufacturing. Following PPAP involves a relatively extensive documentation work. At the internal production, multiple systems are currently being used to handle information about machines, parts, measurement results and deviations. Documents are currently be-ing created and archived in a Windows-based environment where searchbe-ing and updatbe-ing of infor-mation proved to be both time consuming and uncertain. Scania’s production units therefore need a developed working methodology to make the document management more effective in conjunction to the PPAP work.
The aim of this study is to identify potential uncertainties that may have an impact on quality assur-ance in the automotive industry. The study also aims at designing a developed working methodology for Scania CV’s document management in the implementation of PPAP to assure the quality of inter-nally produced parts at Scania.
The result was formulated by a case study of the work processes used in the internal production of Scania’s engine manufacturing. The information has been gathered through qualitative interviews with employees in various departments in the engine manufacturing and through observations in the production. The information about Scania’s process have been analyzed and compared to the litera-ture.
The study resulted in a proposal for an improved methodology in the form of a flow chart to illustrate how the process planes in the motor manufacturing (DM) should use to increase the internal quality assurance of internally produced parts. Potential uncertainties were identified in the areas of; Human, Method and Measurement, where standardized work was considered the most critical contribution to uncertainty in quality assurance.
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Acknowledgements
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Table of Content
LIST OF ABBREVIATIONS ... 0 1 INTRODUCTION ... 1 1.1 Problem description ... 1 1.2 Purpose ... 1 1.2.1 Goal ... 1 1.3 Delimitations ... 2 2 COMPANY DESCRIPTION ... 3 3 METHOD ... 4 3.1 Method approach ... 43.2 Qualitative and quantitative methods ... 6
3.3 Data collection methods ... 6
3.3.1 Interviews ... 6
3.3.2 Observations ... 7
3.3.3 Case study ... 7
3.4 Reliability and validity ... 7
4 FRAME OF REFERENCE ... 8
4.1 The concept of quality and quality assurance ... 8
4.1.1 Definition of Quality ... 8
4.1.2 Definition of quality assurance ... 9
4.2 Industrial standards ... 11
4.2.1 APQP – Advanced Product and Quality Planning ... 11
4.2.2 QS-9000 ... 12
4.2.3 ISO/TS 16949 ... 12
4.2.4 PPAP – Production Part Approval Process ... 13
4.3 Quality assurance tools ... 14
4.3.1 FMEA – Failure Mode and Effect Analysis ... 14
4.3.2 MSA – Measurement System Analysis ... 15
4.3.3 SPC – Statistical Process Control ... 15
4.3.4 MPP – Machining Process Planning ... 16
4.4 Measuring capability ... 17
4.4.1 Machining capability ... 18
4.4.2 Process capability ... 20
4.5 Motivations relation to learning knowledge ... 21
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5.1 Definitions of quality and quality assurance at Scania ... 22
5.2 Scania’s current work on quality assurance ... 22
5.2.1 Production work process at Scania ... 23
5.2.3 Setting and classifying tolerances ... 28
5.2.4 PPAP at Purchasing (SE) ... 31
5.2.5 PPAP at engine production department (DM) ... 32
5.2.6 Measuring ... 37 5.2.7 Solara ... 39 5.2.8 Q-DAS ... 40 5.2.9 Qs-STAT ... 41 5.2.10 O-QIS ... 44 5.3 Conducted Interviews ... 45 6 ANALYSIS ... 47
6.1 Quality assurance in today’s work ... 47
6.2 Uncertainties & traceability ... 54
6.3 Summary of the analysis ... 61
7 RESULTS ... 65
8 CONCLUSIONS ... 67
9 DISCUSSION ... 68
10 RECOMMENDATIONS AND FUTURE WORK ... 70
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List of Figures and Tables:
Figures:
Figure 1. Scania truck form green truck award 2017 (Scania CV, 2017). ... 3
Figure 2. Model of the working method used to perform this study. Adapted from (Ulfsdotter 2014). ... 5
Figure 3. Illustration of the terms quality control, -management, -assurance and - development. Also, visualizing where in production, they are relevant. Adapted from (Bergman & Klefsjö, 2007). ... 10
Figure 4. The quality cost of change depending on which phase you are in (Sörqvist, 2004). ... 11
Figure 5. Illustration of the manufacturing process planning process. Adapted from (Zhang, 1994). ... 17
Figure 6. Visualization of how the different studies are connected to specific distributions and capability studies. Adapted from (Bosch Group, 2004). ... 17
Figure 7. Displays the capability indices of process or machine spread in relation to the tolerance range width. The figure shows two cases with the same capability index, but where the number of defect units varies depending on different centering. Adapted from (Bergman & Klefsjö, 2007). ... 18
Figure 8. Flowchart which generally describes how to conduct a machine capability analysis. Adapted from Bosch Group (2004) according to ISO 16949-3 (2016). ... 19
Figure 9. A model which characterizes a good work development and describes different factors that triggers motivation. Adapted from (Bergman & Klefsjö, 2007). ... 21
Figure 10. Figure describing the overall context to “Manufacturing design and development”, at Scania established as MPP (Manufacturing Preparation Process). ... 23
Figure 11. Description of the working process in the MPP. Adapted from (Scania AB, 2011). ... 24
Figure 12. Overview of the MPP work process in production and its transition phase at Scania engine department (“Production” arrow in figure 10). ... 25
Figure 13. Visualization of different constructions robustness. ... 28
Figure 14. Productions classification of requirements (PCOR) and deviation at DM. It is used to specify what classification a property receives based on its severity and sensitivity. ... 29
Figure 15. Workflow chart for the translation from COR to PCOR at DM. ... 30
Figure 16. Scania’s activity list depending on classification of deviation. ... 31
Figure 17. Description of implementation of the product / process changes. ... 33
Figure 18. Description of how is the process planner conducted the current PPAP work. ... 36
Figure 19. Boxplot diagram over a data point spread (Value on Y-axis and type of property on X-axis). ... 43
Figure 20. Visualization of how the spread of the tolerance should be viewed. ... 43
Figure 21. Example of different colored tolerances. The rule explains that is outside of tolerance, yellow needs adjustment and green is within tolerance. ... 44
Figure 22. Flow model describing an example of a future standardized working method in implementing PPAP at Scania’s engine department. ... 49
Figure 23. Description of different types of uncertainty according to ISO 17450. ... 54
Figure 24. Model which describes uncertainties and the connection between them within Scania and the automotive industry. As a note; green arrows are parts of particular processes. ... 55
Figure 25. Figure visualizing issue with two-point measurement of a diameter (Hedlind, 2017). ... 58
Figure 26. Ishikawa diagram which describes the identified uncertainties in which currently affects Scania’s internal quality assurance based on three factors of the 6M method. ... 61
Tables:
Table 1. List of variation sources from “the 6M”. ... 20Table 2. List of uncertainties and their effects ranked in a descending order. ... 66
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LIST OF ABBREVIATIONS
ArtHur Database for work instructions used and developed by ScaniaAPQP Advanced Product Quality Planning CMM Coordinate Measuring Machine COR Classification of Requirements
DFMEA Design Failure Mode and Effect Analysis DM Engine Production Machining and Foundry ECO Engineering Change Order
EFR Exemption from Requirements
ePPAP eQuality Production Part Approval Process FMEA Failure Mode and Effect Analysis
GRR Gauge Repeatability and Reproducibility
GUM Guide to the Expression of Uncertainty in Measurement
ISO / TS 16949 Standard for quality assurance in the automotive industry. Replaced the old QS-9000. ISO 9001 Management standard for the quality processes and general understanding of quality
and its application in industries.
MPP Machining Process Planning (or Manufacturing Process planning) MSA Measurement System Analysis
PCOR Production Classification of Requirements PCR Product Change Request
PFMEA Process Failure Mode and Effect Analysis PPAP Production Part Approval Process
PRU Production Unit
PSW Part Submission Warrant
PT Industrial Engineer
QS-9000 Quality standard used in the automotive industry, emanated in 2006 when it was re-placed by ISO / TS 16949
RPN Risk Priority Number
SPC Statistical Process Control SQM Supplier Quality Manager
VDA “Verband Der Automobilindustrie” – German Association of the Automotive Industry
VT Workshop Technician
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1 INTRODUCTION
1.1 Problem description
Today a large amount of information is obtained via multiple systems in the automotive industry, and the amount of information is still increasing (Yang, et al., 2006). This contributes to significant time-consuming documentation work. The report studies a truck manufacturer which uses a method named Machine Process Planning (MPP). It is a preparation process which, in an optimal case, can assure the quality of the part. Currently a method called “Production Part Approval Process” (PPAP) is used to complement the internal quality assurance process. This method is used because it is the most optimal way of assuring quality of manufactured parts in the automotive industry. At the same time, there is some uncertainty of how the quality assurance of the internal production will be carried out when there is a lack of clear and consistent guidelines.
Several systems are currently required to manage the entire document flow of the internal production which leads to the human factor having a contributing role in the handling of the information. This can have a negative effect on the parts quality assurance. The transition between these systems in-clude both the handling and transfer of the information. To understand the needs of a new system support, a better understanding and more knowledge about the uncertainties in the current industry is required. The problem is that the current industry is very complex, which makes it harder to reduce the uncertainties that affects the quality assurance.
1.2 Purpose
To define the problem description even further, a few questions were created. Based on the require-ments from the company and within the time frame specified, the main purpose was divided into three major research questions:
- What are the uncertainty contributions from man, method and measurement to the quality as-surance within the automotive industry?
- What are the effects of these uncertainties in quality assurance?
- How can quality be increased, while at the same time maintain or reduce the amount of docu-mentation?
1.2.1 Goal
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1.3 Delimitations
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2 COMPANY DESCRIPTION
Scania AB is one of the world’s leading manufacturer of buses and trucks for heavy transports and was founded in 1911 by merging two car manufacturers named Scania AB in Malmö, and Vabis AB (Vagnfabriks-Aktiebolaget) in Södertälje. The manufacturing of trucks takes place mainly in the pre-mium segment. Scania is a global company that is represented in over 100 countries and today has more than 45 000 employees. The business is predominantly located in Södertälje, where research and development takes place. Scania Group’s headquarters is also located there. Scania’s has three production facilities in Sweden which are located in Södertälje, Oskarshamn and Luleå. Scania also has manufacturing in Europe and in South America.Scania’s corporate culture is characterized by core values that are used internally within the com-pany. These core values are that all individuals and their knowledge must be respected and valued, to always have the customer in focus and that products that the company produces must be of high quality.
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3 METHOD
This study primarily contains an extensive case study that provides an understanding of the content. It made it possible to analyze the potential solutions to the problem. Specifically, to understand the current state at Scania, it is necessary to learn the processes, terms, systems and routines that are used together with the general understanding of Scania’s organization. Deeper expertise was sought through interviews and discussions with supervisors and employees in the specific areas. The docu-ment flow was monitored at Scania from the start to obtain an understanding of the current state.3.1 Method approach
The working methodology which was used is presented in Figure 2. It describes how the working procedure was conducted at the engine department (DM). In the initial phase of the work, an in-depth analysis of the problem description was carried out in which research questions were designed to simplify the problem description. A model which broke down the problem description was designed to simplify the approach (see appendix E). The model defined a more developed background study and guidance. This was to get a better understanding of what is pursued by Scania. Emphasis was early placed on identifying an appropriate working method in order to minimize the risk of wasted time such as unnecessary work and lack of knowledge. Scientific facts were used as a basis to ex-plain the basic concept and methods that were used internally at Scania. To manage data collection of the case study, the following steps were used:
• The company’s intranet (InLine) and local storage servers.
Used for deeper understanding of the company’s procedures and working methods. These two sources of data were the basis for the case study analysis conducted.
• Interviews, surveys and field studies.
Used to describe the current state analysis from a more profound perspective where the ap-proach of the employees could be visualized.
• Observations.
Used to validate what has been said in interviews and get a better sense if what is said in the interviews is realistic or not.
An iterative working process began where the literature review was used as a complement to the un-derstanding of collecting appropriate data and to perform the current state analysis. A feedback loop was implemented since the analysis of the literature study and data collection was conducted in a cy-clic process with the aim to resolve any misunderstandings. The goal of the iterative work process was to provide a description and model of how the engine production department were working at Scania. The model, current state analysis as well as the literature study were used to analyze the po-tential improvements that could be made. To understand how these popo-tential improvements could be valued, an analysis of the effect’s impact was conducted. Studies and verifications with the literature was also performed to verify that the current working process was performed correctly. The final analysis and result were carried out by analyzing the information collected during the project. This study was then concluded and presented as recommendations to Scania.
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Enabling technologies
The following systems have been used in order to conduct this study; qs-STAT, ArtHur, Scania In-Line, Scania’s local file servers.
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3.2 Qualitative and quantitative methods
A qualitative method has been chosen to be used. This is since a qualitative method is preferred for gaining deep insight into the subject of quality controlling of internally produced parts. Therefore, the study was conducted through a qualitative case study with the purpose of studying a specific case, profoundly, instead of doing a study that is possible to generalize (Merriam, 2006).
3.3 Data collection methods
In this part, the main methods that have been used to conduct this study according to the literature will be explained.
3.3.1 Interviews
The definition of an interview, according to Saunders et al. (2012), is a conversation between two or more people, where the interviewer is expected to ask questions to the interviewee(s).
As the report focuses on a more qualitative approach and prioritize qualitative data analysis, the in-terviews of this project work were conducted accordingly. Three different interpretations of qualita-tive interview methods are defined as:
• The qualitative research interview seeks to describe and the meanings of central themes in the life world of the subjects. The main task in interviewing is to understand the meaning of what the interviewees say (Kvale, 1996).
• A qualitative research interview seeks to cover both a factual and a meaning level, though it is usually more difficult to interview on a meaning level (Kvale, 1996).
• Interviews are particularly useful for getting the story behind a participant’s experiences. The interviewer can pursue in-depth information around the topic. Interviews may be useful as follow-up to certain respondents to questionnaires, e.g., to further investigate their responses (McNamara, 1999).
There are four different types of interviews that relate to qualitative interviews. Out of these four, the following two types were used (Saunders et al., 2012):
• General interview guide approach where the intent is to ensure that the general areas of infor-mation are collected from every interviewee. The approach contributes to a more focused conversational approach, but still allows a degree freedom and adaptability in gathering infor-mation from the interviewee.
• Semi-structured, open-ended interview. The same open-ended questions are asked to all inter-viewees. This approach facilitates faster interviews that can be more easily analyzed and compared. It mainly consists of standardized questions that are asked in the same order and may be answered freely.
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the interviewee might feel imposed upon (Saunders et al., 2012). By conducting sporadic and struc-tured interviews with the operators and process planners at DM developed a better understanding of how the work process was is carried out.
3.3.2 Observations
Observations were conducted alongside with some of the general interviews to further visualize how the engine manufacturing department’s work flows and functions. The primary focus of data collet-ing lay on gathercollet-ing as much information as possible in order to answer the research questions. A qualitative observation focuses on bringing out and knowing all the intimate details about every as-pect related to the subject. The qualitative observation was done on a more personalized level in or-der for the participants to be able to appoint specific questions to the interviewer (Taylor et al., 2015). To conduct qualitative observations, it was necessary to maintain a low standardized way of observing. That means to maintain an open perspective of behavior and observations that you are in-terested in. This observation was also conducted without a hypothesis which lead to that it was hard to know what behavior you wanted to observe. Therefore, the focus must be on the research ques-tions that have to be answered (Bell, 2015). The observaques-tions conducted at the engine department and the information provided the basis for the design of the current state analysis.
3.3.3 Case study
The case study that has been carried out had the ambition to describe the complex structure and func-tionality of a manufacturing company. The purpose of a case study is to add content that extend the previous research and therefore a literature study is necessary. It is a qualitative research method that has the intent to examine current real-life situations. This should then be analyzed and used to gener-ate new ideas. (Hamel et al., 1993). According to Yin (1984), a case study research method is de-fined as:
“an empirical inquiry that investigates a contemporary phenomenon within its real-life context; when the boundaries between phenomenon and context are not clearly evident; and in which multi-ple sources of evidence are used”.
3.4 Reliability and validity
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4 FRAME OF REFERENCE
In this chapter, the results of the literature study are presented. It is related to the problem formula-tions and baseline information needed for the project.4.1 The concept of quality and quality assurance
This part will explain the fundamentals of what quality and quality assurance is according to the lit-erature.
4.1.1 Definition of Quality
The word “Quality” originates from ancient Greece and means nature or condition.
According to Reeves and Bednar (1994), there is not a general definition for the word quality that can be applied for all types of products or services within all industries. Different definitions can be considered to be appropriate in different circumstances and must therefore instead be adapted de-pending on the context in which it is used (Dale et al., 2007).
The manufacturing and development of products in a company means that multiple functions have to be involved. This means that there may be different views on what is considered to be the main goal of the product (Foster, 2004).An uncertainty within the organization may exist regarding the defini-tion that should be considered to have priority when developing the organizadefini-tion’s internal definidefini-tion of quality (Whetten, 1996). This therefore requires consideration regarding the occurring differences of various quality definitions and where the term should be applied. The main reason that companies choose to define their own interpretations of quality is due to the difficulties encountered in identify-ing the external customer’s preferences, which can be costly both from a financial and time perspec-tive. The existence of several different definitions of quality can lead to problems in the organization if these cannot be clearly communicated. By sharing the same definition between different depart-ments, it is possible to work toward a common goal and through a deeper understanding of the user’s perspective on quality which can lead to product improvements (Juran, 1998).
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Application of quality in industry
In the second edition of Quality control handbook, Juran (1998) defined eight primary applications of the term Quality in industry:
1. Marketplace quality – Describes to which extent or how well a specific product meets the needs that a customer may have.
2. Quality of design – Describes the extent of how well a product category can maintain the ability to generally satisfy people.
3. Quality of conformance – Describes the extent to which a product conforms to product speci-fication or design.
4. Consumer preference – Describes the extent to which a product is preferred over a similar grade or competing product based on comparative testing on consumers.
5. Quality features – Characteristics of a specific product (i.e., performance, appearance and product life span).
6. A vague expression of general excellence but without being specific enough to be classified. 7. The name of a function or responsibility in industry, related to achievement of quality of
product.
8. The name of a specific department in a company.
4.1.2 Definition of quality assurance
In the automotive industry, it is very challenging to ensure product realization in the shortest possible time while retaining costs at a minimum. A requirement is also to maintain high quality products to a low price and this puts a lot of pressure on the realization process. The companies are required to spend a minimum amount of time and resources in order to increase business efficiency, but the quality is crucial for being able to compete. Quality assurance is used to make sure that the company fulfils the customer’s desire (Curkovic, 2000). The term is very important due to the fact that cost is exponentially increasing the later you detect flaws in the process of creating a new product. Sörqvist (2004) also points towards that preventative actions are necessary in order to manage quality assur-ance the same way it is used in production.
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Figure 3. Illustration of the terms quality control, -management, -assurance and - development. Also, visualizing where
in production, they are relevant. Adapted from (Bergman & Klefsjö, 2007).
According to ISO 9000 (2000), quality assurance is: “Part of quality management, focused on providing confidence that quality requirements will be fulfilled”.
In order to assure that the desired quality of the products is achieved, there are several standards that are used in the automotive industry. ISO 9000 defines the quality standards and general rules on quality management all industries. QS 9000 is based on five pillars of quality (PPAP reference man-ual, 2006). These pillars are (Kušar et al. 2014):
• Advanced Product Quality Planning and control plan (APQP). • Failure Mode and Effect Analysis (FMEA).
• Statistical Process Control (SPC). • Measurement System Analysis (MSA). • Production Part Approval Process (PPAP).
ISO/TS 16949 replaced QS 9000 and is based on the ISO 9000 standard (Bevilacqua et al., 2011). However, ISO/TS 16949 is specific for the automotive industry in terms of quality management sys-tems (Kušar et al. 2014).
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Figure 4. The quality cost of change depending on which phase you are in (Sörqvist, 2004).
4.2 Industrial standards
This chapter will explain the basics of the standards that sets the framework for how the quality and quality assurance at Scania should be defined as well as managed.
4.2.1 APQP – Advanced Product and Quality Planning
Advanced Product and Quality Planning and control plan (APQP) is a basis or guideline for produc-ing a product quality plan that is used to support the development of new products or services. It is designed to structure processes in order to ensure that customer satisfaction is achieved. This is achieved when the supplier understands the customers’ requirements, end-user and consumer (APQP reference manual, 1995).
The benefits achieved by following the APQP guidelines include:
• A reduced complexity arising from the product quality planning for suppliers and customers. • APQP is used as a tool to facilitate the dissemination of information from the supplier
regard-ing the product quality plannregard-ing requirements to its subcontractors.
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The APQP process consists of five different phases consisting of several inputs and outputs which vary depending on customer needs and the production processes. The five phases are the following:
1. Plan and define.
2. Product design and development. 3. Process design and development. 4. Product and process validation.
5. Start-up, feedback assessment and corrective action.
The initial phase examines the internal and/or external customers’ needs so that the customer’s qual-ity approach and goals can be defined. This is accomplished by examining the collected data in the form of market surveys or information corresponding to the voice of the customer (APQP reference manual, 1995).
4.2.2 QS-9000
QS-9000 is an established industry standard for quality management systems. It is an extension of ISO 9001:1994 where new additions were carried out to clarify the requirements that are specified in the ISO 9001 standard (Eriksson et al., 2001).
QS-9000 was developed in cooperation between the three leading auto manufacturers in the US: Chrysler, Ford and General Motors. The main purpose of the standard is to establish a common ap-proach for the demands on the suppliers by providing supporting documents in order to assist in meeting the specified requirements in the automotive industry. With the support of QS-9000, the suppliers should develop a quality assurance system as well as routines that can ensure; continuous improvements, prevention of potential failures and reduction of unnecessary work (Eriksson et al., 2001).
The requirement of QS-9000 applies to: • Suppliers of semiconductors.
• Suppliers of tools, machinery or equipment.
4.2.3 ISO/TS 16949
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4.2.4 PPAP – Production Part Approval Process
PPAP (Production Part Approval Process) is used to describe a number of general quality and pro-cess requirements to be imposed in connection with part manufacturing. The application of the PPAP is a way to assure the quality of the production processes in line with the ISO/ TS 16949 standard, which in turn is adapted to the ISO 9001 standard. The general purpose of the PPAP is to provide ev-idence that all customer specified requirements are properly understood by the supplier and that the production has the potential to consistently meet those during the corresponding full production (PPAP reference manual, 2006). The completed documentation is intended to be used by the cus-tomer as a basis in order to illustrate whether the supplier’s process can be considered sufficiently capable of manufacturing the specific product. PPAP is also intended to be used for product and pro-cess validation, thus leading to a feedback loop, where corrective actions are implemented. After that the PPAP documentation has been completed, the following status can be obtained; Approved, In-terim or non-approved. Upon receiving an inIn-terim status on the PPAP documentation, additional in-formation may be requested or alternatively wait for further decisions.
One requirements set on the PPAP manufacturing process for produced parts is that the PPAP docu-mentation should be carried out from a significant production run. The selection should be made from the production that has taken place between one to eight hours of production. During this pe-riod, at least 300 parts should be consecutively selected unless otherwise stated.
The PPAP manual describes in detail the requirements for obtaining an approval for series delivery. It also describes requisite documents and when the customer has to give its approval.
An application for serial delivery approval from the supplier should be implemented in the following situations:
• When introduction of new products or parts takes place that previously have not been sup-plied by the specific customer.
• When a correction is carried out on a deviation of a part in a previously completed applica-tion.
• When a modification has been performed on a product with respect to specifications, design, or material changes.
• When conditions changes in the productions process and for parts and materials.
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4.3 Quality assurance tools
This chapter will go through some of the most fundamental tools in order to assure the quality at Scania.
4.3.1 FMEA – Failure Mode and Effect Analysis
“Failure Mode and Effect Analysis (FMEA) is an engineering technique used to define, identify, and eliminate known and/or potential problems, errorsfrom the system, design, process, and/or service before they reach the customer” (Omdahl, 1988).
According to (Ben-Daya et al, 2009), it is clear that from that definition, FMEA is a systematic meth-odology intended to follow three different activities:
1.
Identify and recognize potential failures including their causes and effects.2.
Evaluate and prioritize identified failure modes since failures are not created equal.3. Identify and suggest actions that can eliminate or reduce the risk of the potential failures from occurring.
Failure mode and effects analysis (FMEA) which is often called failure modes, is a very useful tech-nique for reliability analysis. It involves a systematic review of a product or process, its function, failure modes, fault causes, and consequences of faults. The technique breaks down the failure into different pieces that are used to pinpoint where it occurs and the reason for its occurrence. An FMEA can be used in different applications. Quantitative and relatively rough analysis can be used already in the planning and definition phase of a project. In the design and development phase a more devel-oped FMEA can be used in order to control different reliability activities. Such FMEA can serve as an excellent basis for design reviews. These types of FMEA are called Design FMEA (DFMEA). In connection with the production preparation, a Process FMEA (PFMEA) is a way to evaluate the manufacturing process. In general, the technique is used in the manufacturing process to study the product failures and how the failures can be caused by disruptions in the manufacturing process. The PFMEA is used later as a basis for the organization in the process control (Bergman & Klefsjö, 2007).
To rate each potential failure mode and effect in an FMEA, there are three factors to consider (Ben-Daya et al, 2009):
• Severity: the consequence of the failure when it happens.
• Occurrence: the probability or frequency of the failure occurring.
• Detection: the probability of the failure being detected before the impact of the effect is real-ized.
These factors multiplied defines the risk priority number (RPN) which reflects the priority of the fail-ure modes that are identified. The formula for RPN is (Ben-Daya et al, 2009):
Risk Priority Number = Severity x Occurrence x Detection.
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4.3.2 MSA – Measurement System Analysis
It is very common that errors occur when a measurement is being carried out. If you limit the investi-gation to a sub-sample and deviate from the overall perspective, you will get a sampling error. Non-response errors occur when you fail to measure all the devices that you intended to measure, and when those devices that are not measured differ from the ones that are. Measurement errors that are outside accepted variation, can occur as a result of deficiencies in measurement methods and measur-ing instruments. These examples all effect how accurate the data will be and if the measurements are uncertain, difficult or critical, a Measurement System Analysis (MSA) often is performed. A com-plete MSA can consist of studying the current measuring method from the following perspectives (Sörqvist, 2004):
•
Accuracy is a measure of whether the measured value matches with the actual value.•
Repeatability indicating whether the same results would be obtained if the measurementis repeated by the same person.
•
Reproducibility involves studying whether the same results would be obtained if the measurement is repeated by another person.•
Stability describes how stable the measurement process is over time.•
Suitable measuring scale involves examining the selected measuring scale suitable for the selected measurement situation.By conducting MSA, you will be able to identify the process capability and therefore know how reli-able your process really is. The standard of MSA define capability as (MSA reference manual, 2010):
“An estimate of the combined variation of measurement errors (random and systematic) based on a short-term assessment of the measurement system”.
The quality of the data is dependent on how far or close the measurement is to the master value for the characteristic (MSA reference manual, 2010).
4.3.3 SPC – Statistical Process Control
Statistical Process Control (SPC) is a process control system which can be described as a feedback system (SPC reference manual, 2005). As the Japanese quality expert Kaoru Ishikawa said in 1982, “we live in a world of dispersions” (Bergman & Klefsjö, 2007).
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The purpose of using SPC is to address as many contributions of variation as possible and then elimi-nate them. When a more stable process, with a small variation is reached, the purpose is changed to either maintain or improve the process (Bergman & Klefsjö, 2007). Measurement systems are critical to proper data analysis and they should be well understood before process data are collected. When such systems lack statistical control or their variation accounts for a substantial portion of the total variation in process data, inappropriate decisions may be made. (SPC reference manual, 2005). The SPC’s purpose is mainly based on information from the process (Bergman & Klefsjö, 2007):
• Identify distinct causes of variation and eliminate them.
• Monitor the process when it is in statistical control so that new noticeable causes of variation are not introduced without the operator's knowledge.
• Continuous data capture from the process so that new causes of variation can be identified as noticeable, and then eliminated.
4.3.4 MPP – Machining Process Planning
The complete manufacturing process comprises the chain process from raw material to the desired product (see Figure 5). It involves either the assembly process planning or machining process plan-ning. Machining process planning aim at the process that is carried out in the individual production machines while the assembly process planning concerns how multiple components are assembled to form a main component (Zhang, 1994).
According to Dong et al., (1996), the manufacturing process planning is the link between the design and manufacturing processes where information exchange occurs. Zhang (1994) believes that the manufacturing process planning can be defined as the specific methods for manufacturing of parts, in a financial or competitive way. Initially, machine process planning is conducted by using geomet-rical characteristics, tolerances and materials in order to determine the optimum machining
se-quences based on available equipment. The information that is considered to be of importance for the process planning is the following:
• Design data – Information consisting of single component- and assembly drawings presented in most cases. CAD models are also used in some cases where design data is to be presented. • Quality requirement data – Information that influences the choice of tools, fixtures and
equip-ment in the process planning.
• Production information – Information that is used for various process plans when similar products requires different types of production.
• Raw material – Information related to the raw materials used as well as the company capacity of raw material.
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Figure 5. Illustration of the manufacturing process planning process. Adapted from (Zhang, 1994).
4.4 Measuring capability
A process capability is decided by the statistical distribution that the product quantity follows. When a process is in statistical equilibrium (stable), the selected distribution can in many cases approxi-mately be described by a normal distribution. If the process is not stable, the capability measure can-not be recognized since there is no knowledge of what the distribution will look like. A capability study requires knowledge about what is going to be studied. Both the SPC reference manual (2010) and the APQP reference manual (1995) distinguish between long (process capability) term and short term (machine capability) studies. Figure 6 displays how the selection of what capability study may be selected.
Figure 6. Visualization of how the different studies are connected to specific distributions and capability studies.
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In order to decide the capability, the average value (µ) of the natural spread of measurements is re-quired. Figure 7 describes a certain capability of producing units (Cp or Cm) within the tolerance
lim-its (ULTL, TUTL) (Bergman & Klefsjö, 2007).
Figure 7. Displays the capability indices of process or machine spread in relation to the tolerance range width. The
fig-ure shows two cases with the same capability index, but where the number of defect units varies depending on different centering. Adapted from (Bergman & Klefsjö, 2007).
4.4.1 Machining capability
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Figure 8. Flowchart which generally describes how to conduct a machine capability analysis. Adapted from Bosch
Group (2004) according to ISO 16949-3 (2016).
When the consecutive parts have been measured, the measurements should be analyzed. An analysis is used to see if the values are normally distributed, how they are relative to the target value and the spread they have. If you do not find the values to be normally distributed, then there is a symmetrical variation which means that the study is unstable. Continued capability study is therefore meaning-less.
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Examples of variation sources (Bosch Group, 2004), (Nielsen, 2016) can be seen in Table 1. Man Personnel, Experience, Shift changes
Machine Speed, Feed rate, Tools, Cycle times, Coolant flow rate and temperature, Pres-sures, Current (in the case of welding equipment), Power (in the case of laser welding), Change status (in the case of optimization measures).
Material Semi-finished parts, rough parts or blanks from different lots or manufacturers. Method Run-in (warm-up) time of the machining facility before sampling, Differing
pre-machining or production flow.
Measurement Resolution and spread of measuring instrument
Mother nature Room temperature (temperature changes during production of the sample), (Environment) Relative humidity, atmospheric pressure, Vibration acting upon the machining
facility, Location of the machining facility in the building (story), Unusual events.
Table 1. List of variation sources from “the 6M”.
4.4.2 Process capability
Process capability is a long-term study where evaluation of parts manufactured is done over a longer period of time and represent the variation in series production. During a process capability analysis, all external factors that affect the production process over a longer operating time have to be consid-ered (Bosch Group, 2004). These factors include those discovconsid-ered from doing a machine capability study (see Table 1).
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4.5 Motivations relation to learning knowledge
Knowledge is such a powerful tool that already the American psychologist Liknert (1961), for exam-ple, drew the conclusion that the leaders who only focus on getting the work done is less successful than those that also put emphasis on the social relations in the workplace. Hackman & Oldham (1976) believes that work is characterized by wide use of resources as well as complete and mean-ingful tasks with feedback of results to create the conditions necessary for motivation and engage-ment.
A survey conducted in 1987 by the American Society for Quality (ASQ) showed that American com-panies felt that the greatest potential of quality improvement measures were the "soft" side, were the soft side is aimed at the business and the worker (Bergman & Klefsjö, 2007). This was also con-ducted in Sweden nearly ten years later when the results showed similar results (Axelsson and Forsberg, 1998). A visualization of triggering factors of motivation can be seen in Figure 9.
Figure 9. A model which characterizes a good work development and describes different factors that triggers motivation.
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5 CURRENT STATE ANALYSIS AT SCANIA
This chapter describes the current state at Scania in terms of quality and quality assurance; how Scania defines quality, how they assure that their parts maintain the necessary quality and the pro-cess that is used in order to succeed with this.5.1 Definitions of quality and quality assurance at Scania
There are different meanings of the terms quality and quality assurance within Scania. Their internal intranet called Inline defines these terms in a general way.
The general established definition of quality defined by Scania’s intranet system Inline is: “The degree to which a set of inherent characteristics fulfils set requirements”.
The concept of quality assurance is defined on Inline as:
“Part of quality management focused on providing confidence that quality requirements will be ful-filled”.
5.2 Scania’s current work on quality assurance
This section describes Scania’s current work on quality assurance of internally produced parts. It describes the responsible people, how they conduct their work, and what systems and methods that are used in order to achieve high quality.
Process planner
The role of the process planner in quality assurance at the engine department (DM) is to possess the knowledge of how to construct and increase the efficiency of the production. Process planners are also intended to support the design department’s work in order to adapt the production process, or in few cases, the part. If problems or deviations occur, provided that the process plan and other support-ing functions are worksupport-ing properly, the responsibility falls on the process planner. If such thsupport-ings hap-pen, it is necessary to create improvement activities by analyzing deviations of quality in production. This is conducted by either analyzing the capability deviations or the measurements that are received from the measuring room. A process planner should also support the internal quality team by provid-ing feedback in terms of occurred deviations to internal and external suppliers.
Industrial engineer (PT)
The industrial engineer’s responsibility in terms of quality at the DM department is to implement projects that improve efficiency. To identify and carry out layout improvements, as well as work-place designs, are also part of the responsibility. Further, the industrial engineer’s responsibility is also to support the process planner during introductions of an ECO (Engineering Change Order) as well as with product development projects.
CMM operator
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To operate a CMM, knowledge about metrology, related standards and machine functionality is nec-essary. While preparing measurements, experience of the machines behavior and how to program the movement is required by the operator.
Workshop quality technician (VTQ)
The workshop quality technician is responsible for compiling and reporting internal quality devia-tions and supplier non-conformances at DM, such as deviadevia-tions from external customers over the past 24 hours, as well as quality deviations from DM. VTQ supports the departments in the daily contact with the internal customer through continuous contact with the industrial engineer at the dif-ferent departments. VTQ is also responsible for the training of routines when changes are made or introduced.
Workshop technician (VT)
The role of the workshop technician (VT) is to act local support for the process planners in the every-day production as well as to represent the key competence in the work with corrective measures. They are also responsible for participating in the development of the change request. The VT is in-cluded in the local management group and cooperates with surrounding functions in order to improve the quality of the product and production. They should actively work preventive and development with quality assurance.
5.2.1 Production work process at Scania
Initially, machine process planning (MPP) is applied and a lot of steps are performed before the ac-tual production can start. The initial part is developed early and a lot of planning, investments, set-ting of requirements, method development as well as defining steps for how production should func-tion are created before manufacturing actually starts. The map in Figure 10 displays how the product realization comes to life through three steps (blue arrows), with certain “tools” and in a cohesive and standardized way of defining tolerances (GPS).
Figure 10. Figure describing the overall context to “Manufacturing design and development”, at Scania established as
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The MPP has a purpose of supporting the process planner with a standardized way of working for all production units at Scania. The model is used to describe the optimal approach available to imple-ment a process plan, which has the intent of ensuring a parts quality, according to its design (Scania AB, 2011). In case any part changes, only applicable parts of the model are used. The MPP model consists of six stages and is described in the Figure 11:
Figure 11. Description of the working process in the MPP. Adapted from (Scania AB, 2011).
1. The initiation phase describes why an initiation of a process plan takes place and consists mainly of four causes:
• Quality
Quality problems linked to selected manufacturing method or material of an ongoing process.
• Product development
Product development changes due to requests or requirements from production, devel-opment or customer.
• Manufacturing method
The use of new production equipment or production methods can cause a change in the process planning.
• Continuous improvement
Improvement work related to the improvement group’s work or corrective action within the framework of the company’s production system (SPS).
2. The pre-study phase describes a rough draft of the process planning department’s work in a work plan, which should result in a basis for further work and product development. The pro-cess planner should conduct a meeting with the design department at an early stage during the pre-study to ensure that late changes in the project can be reduced. An audit should be held where the production requirements and the production method are required to be specified to ensure the producibility of the part. A working documentation is expected to be created from the meeting with the design department and should be used in the assessment of the follow-ing:
- Calculation of production capacity.
- Cost evaluation for the introduction of the part, as well as the possible investment needs.
- Time schedule for development, verification and the introduction of the part.
3. During the development phase, the process planner completes a preliminary processing draft consisting of the following:
- A basis for economical calculations.
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Continuous communication between design and process planning department should be established to ensure that there are no uncertainties and to discuss the progress of the work.
4. During the verification phase, the preparatory work, as well as the verification of the manu-facturing process, is completed. The verification is done when the process meets the require-ments of mass production. A final validation is done by signing the PSW (Part Submission Warrant) document which is then reviewed and approved by the workshop manager when signed.
5. In the introduction phase, the responsibility for the serial production is handed over from the process planner to the production line.
6. During the end phase, a confirmation that the responsibility for the takeover of the production has been completed as well as all relevant process and quality assurance documents that have been implemented, is executed.
However, this report focuses on a running production line where the start of the process often is trig-gered by some kind of change in the process. Since the process is very complex, the overall produc-tion process at Scania requires many different systems. At the engine department alone, there are five different systems for managing data and several different software’s that are used to support the management of the data. There are however a lot more systems that are used to support different ar-eas which are not considered in this case. A systematic overview of the MPP process work can be seen in Figure 12.
Figure 12. Overview of the MPP work process in production and its transition phase at Scania engine department
(“Production” arrow in Figure 10).
Each individual operation level (except for “ExpertCAD”) is further explained below and is visual-ized in flowcharts which can be seen in appendix F.
Catia and Enovia
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reason for this is that some process planners prefer this program since it is simple to use. However, Catia is used by both the design department and the majority of the manufacturing department. The design department is responsible for designing parts and make changes to existing parts. These designs are then sent as a 3D CAD models to the production department. They use the CAD software for designing each model after every operation step in the production line (in-process part models). These models are later used for generating in-process part designs in a software called ArtHur. All data that is created is stored in the PLM (Product Lifecycle-Management) software Enovia. This sys-tem is integrated in Catia to easily manage the CAD files (both 3D models and drawings).
ArtHur
ArtHur is a database that is used for creating and maintaining manufacturing documents (work in-structions) and documenting process information, such as setup time, run time per unit, measurement frequencies and so on. Data such as this are prepared before production starts which is outside the scope of this project. However, it is still maintained and updated by the process planner. The ArtHur system is used by the process planner to store the correct work instruction that is used in the machin-ing process. It has a graphical interface which simplifies the usage of a structure and it is used to sep-arate different manufactured parts. Relations in the structure are constructed towards a part with an input and output of manufacturing documents. A system for handling this kind information is neces-sary for the process planner in order to keep track of different parts’ specific instructions for manu-facturing. However, there is no specification of how every document under each part should be de-signed. For example, rig documents or process documents drawing detail can differ from process planner to process planner. This is due to a lack of coordination during the development of the sys-tem. ArtHur does not distinguish between work instructions and process requirements. It only allows the process planner to store the different documents according to a logical structure chosen by the individual. This leads to that process planners only knows that they follow a specified measurement which leads to a certain quality. During the time when production is running and no frequent errors occur, changes in ArtHur are not often required. However, some cases require updates in the system. For example, when a change in the part, when a new tool is to be used, when a part property is going to be machined in another operation, or when the measurement frequency is changed.
If a part change is necessary (triggered by an ECO), the process planners starts by editing and saving any potential changes to the in-process part drawings from Catia in a TIF format, which can be im-ported into ArtHur. If any tolerances are changed by the design department, the in-process part veri-fication tolerances (process tolerances) then has to be re-calculated and include all potential spreads that may occur. However, if it does not require a change in the part, the system can just be updated instantly.
Calypso
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When an actual measurement has been completed, the results are converted into a specific format which can be stored and managed through the Q-DAS SQL database. In some cases, the measure-ment program causes read errors which will be logged and stored in a separate folder in a local data-base. This issue is not always solved since some measurements are just re-measured, or that there is lack of knowledge of how to handle it. An example of an error is when the name of a property is used twice which no measuring machine can detect (except for the Calypso machines). If the data is successfully completed, it is moved to Q-DAS SQL database through an upload folder.
Text editor (Generation of NC code)
There are two different systems that are used to write the NC-code (machine program). These are Notepad and a Computer Aided Manufacturing (CAM) software called AdCAM NcS 2016. This soft-ware is used since no post processor is required because the tool designer generate the machine pro-gram by writing the code on his own. The NC-code can be simulated in 2D to increase the under-standing of the toolpath and program behavior. Notepad is a simple text editor which is used as an alternative to NcS. Both software builds on the same principles and demands that the tool designer writes the machine program directly into the text editor. In some machine programs, there are com-plex loops which lead to that the simulation in NcS is hard to understand. Therefore, some simula-tions in the CAM program is not useful. However, it provides some assistance (e.g. preventing too fast z-axis movement).
A tool designer is responsible for generating the NC-code. The tool designer uses the process in-pro-cess part models that have been designed by the proin-pro-cess planner in order to program the code (spe-cific toolpaths, tools, tool speeds etc.) A more detailed procedure for how this is done can be seen in appendix F. The primary idea is that the program needs to be tested, changed and optimized a few times before it can be released for manufacturing. When this requirement is met, and has been ap-proved by the process planner, the NC code can be stored and set as “free” (downloadable from the machine) in a storage system called RWT.
CNC and CMM
When the preparation of a line is completed, it is time to start the manufacturing. This means that several operations are carried out in CNC machines during processing of the part, and that measure-ments are conducted in CMM machines, to assure that the products are according to specification in the end. During the start-up in the early stages, the process is a bit different in relation to when the production has been running for a longer period of time. A model of the flow can be seen in appen-dix F, where the flowchart represents the process when a production line has been running for a longer period of time. This process is managed and controlled by the process planner, industrial engi-neer, engineering technician, and CMM operators.
Q-DAS
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5.2.3 Setting and classifying tolerances
At Scania, classifications are done in two steps. Initially, the design department is responsible for set-ting the frame of reference and defining the classifications according to how severe a property failure would be. Thereafter, the production engineering department is responsible for classifying all the measurements with the process capability aspect in mind.
The classification is supported by two internal standards, STD 3944 (which specifies how different requirements should be applied) and STD 4178 (which specifies how the legal requirement should be applied). Together they form the complete standard for how Scania uses classification of require-ments (COR) which is used by every production unit (PRU) at Scania.
Tolerancing at the design department
To fully understand how the tolerances are set in production, it is necessary to understand how they are created at the design department. Initially when a drawing is created, the design department is re-sponsible for classifying the tolerances with C, M, S and L requirements which are defined as:
• S – Small impact. • M – Major impact. • C – Critical impact. • L – Legal requirements.
In the process of classifying the tolerances, the structures sensitivity and what impact a deviation from a requirement may be is estimated based on the requirements from the customer.
Figure 13 displays how different constructions (curved colored lines) behave according to a tolerance property. Sensitivity depends on how close to the requirement limits the function and thus customer requirements is compromised. In other words, if the construction is robust. The green curve repre-sents the most robust construction while the blue curve reprerepre-sents the most sensitive construction.
Figure 13. Visualization of different constructions robustness.
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have if the construction breaks. A list of the classification of requirements (COR) has been defined for the design department which is used by the designer as a frame of reference.
Tolerancing at the engine department (DM)
During the process planners work process, many work instructions are necessary in order to help the operators to successfully do their job. These work instructions include several datasheets containing information of; in-process part verification tolerances, measurement frequencies, specific tool num-bers (both for control measurements and for machining). In order to get the in-process part verifica-tion tolerances, the process planner have to preform calculaverifica-tions from the design drawing specified by the design department. This has to be done for every operation step in the manufacturing line. In short, the process planner looks at the drawing and removes all the potential spread from the process of manufacturing the part. This is done by using tolerance chain analysis methods, working your way back from the finished part. Many references that are used in the design drawing cannot be used since some references used in the drawing, have not yet been machined in the specific operation. By doing this the process planner can see exactly how the part should look like and what tolerances the piece have to be within in order to make sure that the final tolerance requirements are met.
When the tolerances have been set for each operation, the process planner is responsible for classify-ing all the measurements on the drawclassify-ing that is goclassify-ing to be measured in the measurclassify-ing room. The process planner categorizes the measurements and makes sure that the most critical ones are meas-ured primarily. This is done by using a 10-graded scale of seriousness in order to set the new classifi-cations according to manufacturing demands. All of the measurements, on an engine block for exam-ple, cannot be measured since it has between 2000 – 4000 geometric characteristics.
Currently, within Scania, the classification system of requirements and deviations used at DM con-sists of a matrix (Figure 14), a severity scale (Appendix C), and documented instructions for how to use this scale.
Figure 14. Productions classification of requirements (PCOR) and deviation at DM. It is used to specify what
classifica-tion a property receives based on its severity and sensitivity.
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The documentation support on classifications consists of; part drawings, EFR (Exemption from re-quirement) history, D-FMEA, design NM (Engineering Development), assembly requirements and the severity scale. Every specific property is ranked from 1-10 depending on which effect a potential failure has on the specific property (similar to what is done in an FMEA). Critical measurements that are classified as 7-10 should be prioritized, the remaining properties (1-6) are prioritized in a de-scending order. Process properties that are related to the reference plane, locating holes, planning surfaces or clamping surfaces in the subsequent process steps or operations should also be priori-tized. Reason for this is that these properties can have a major impact on subsequent features process capability and quality.
Every requirement has a sensitivity which is described by the deviation of the tolerance range as a percentage. The sensitivity in Figure 14 is calculated in the CMM and is logged as a parameter in the Q-DAS database. However, this value is stagnated the longer production has run which is one reason why significant production run is important. The severity is selected after the process has stabilized and a requirement can be set according to what the production department can deliver. A description of the workflow when specifying PCOR can be seen in Figure 15.
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When the classification is set at the production department, an assessment is made of if the part can be approved or not. If the part is approved, it can be shipped to the internal customer (assembly de-partment). In cases when it is not approved, the deviation has to be corrected. How the different clas-sifications should be handled is listed in Figure 16.
Figure 16. Scania’s activity list depending on classification of deviation.
5.2.4 PPAP at Purchasing (SE)
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is being delivered. Based on this information, it is determined what kind of documentation the sup-plier should deliver.
The ePPAP documentation is conducted by external suppliers and are stored in a ePPAP system called eQuality. The eQuality system is used in Scania’s work with quality assurance amongst the customer, supplier, subcontractors and within Scania. The system is also used between internal sup-pliers and customers in order to handle deviations. If any changes are made to the system, the PPAP requires an update. This ensures that the documentation is up to date and that the specified part prop-erties that each department receive, is correct. The internal production departments at Scania do not receive any detailed information from the purchasing department regarding the PPAP documenta-tion, that has been provided by the external supplier. They only receive information if the PPAP has been approved or not. This is used as an acknowledgment that the internal production process within Scania can begin. However, the documented information can be given in individual cases to the con-cerned persons when they are in need of further information during a root cause analysis for exam-ple.
5.2.5 PPAP at engine production department (DM)
Scania is actively working on establishing produced parts of high quality. To ensure that the parts maintain high quality, the production department is using a proprietary version of the production part approval process (PPAP) for quality assurance of self-manufactured parts. A PPAP system is used as a quality assurance system to ensure that the process planning department has not missed anything in their work. PPAP is also used to document and analyze the part features and the steps that ensure that changes are carried out properly. In order to maintain traceability for every specific PPAP document, a parts article number is used. These documents are then stored in a folder structure on a global Sca-nia server.
The engine engineering department (DMT) currently uses an internal PPAP routine called the “PT manual” which is described in Scania’s intranet (“Inline”). This manual is included as part of the in-ternal management of the motor department (DM) and is used to document information about prepa-ration and production of technical instructions. Each department manager oversees the various points in the PT manual. It is meant to serve as support for process planners’ work process. It also has the purpose of describing how PPAP should be carried out from a process planner’s perspective, either when a part changes or when an introduction of a new part is to be approved to assure quality. The manual describes how PPAP should be implemented and other general instructions that relates to the process planners work. The PT manual also describes how changes of the part should be imple-mented in the ArtHur system.
Scania’s routine for ECO, PCR and EFR
