Lecture Quality Management

Transcription

1 Lecture Quality Management 11 Quality and Information Prof. Dr.-Ing. Robert Schmitt Quality and Information L 11 Page 0

2 Contents Pyramid of Knowledge Quality Control Loops CAQ - Computer Aided Quality Management Introduction of CAQ Systems Page 1 Literature: Pfeifer, T.: Qualitätsmanagement Strategien, Methoden, Techniken; Carl Hanser Verlag; München, 2001,ISBN Pfeifer, T.: Quality Management Strategies, Methods, Techniques;Carl Hanser Verlag; München, 2002, ISBN Pfeifer, T.: Praxisbuch Qualitätsmanagement Aufgaben, Lösungswege, Ergebnisse; Carl Hanser Verlag; München, 2001, ISBN Masing, W.: Handbuch der Qualitätssicherung; Carl Hanser Verlag; München,1988, ISBN Erb, M.: Methodik zur modellgestützten Planung von CAQ-Investitionen; Shaker Verlag GmbH; 1996, ISBN Mutz, M. u.a.: Marktspiegel CAQ-Systeme; Sondereinband - TÜV Rheinld.; Kln., 1998, ISBN Platt, A.: Rechnergestütztes Qualitätsmanagement für Chargeprozesse in industriellen Dienstleistungsunternehmen; Verlag Dr. Kovac, 1998, ISBN Quality and Information L 11 Page 1

3 Pyramid of Knowledge Action Decision Knowledge management Information management Data management Knowledge Information Data Signs Pragmatics (networking with context and know-how) Semantics (meaning) Syntax Quelle: Erweiterung zu Davenport Page 2 Pyramid of Knowledge The signs build the bottom of the pyramid of knowledge. A sign is the smallest accessible data element. It can consist of numbers, letters or special signs. In combination with syntax, signs become data. Data consist of texts, pictures etc., which can be seen, measured and structured. With the help of information, relations between problems can be recognised. Thereby, information helps achieving the aim. Knowledge is more complex than information and data. It is a mixture of structured experiences, ideals, context information and know-how, that builds a structural frame for the evaluation and integration of new experiences and information. An action is the activity that follows a decision based on knowledge. Quality and Information L 11 Page 2

4 Pyramid of Knowledge - Example Signs: Data: Information: Knowledge: Action: 1, 0, S, G, W, T, R, E, N, I, D, N, H The signs above mean wind strength 10 by using the right syntax (in this case the order of the signs) Wind strength 10 means: a thunderstorm appears. Experiences like my boat can capsize are associated. Activities like fixing the boat at the footbridge are derived. Page 3 Quality and Information L 11 Page 3

5 Contents Pyramid of Knowledge Quality Control Loops CAQ - Computer Aided Quality Management Introduction of CAQ Systems Page 4 Quality and Information L 11 Page 4

6 Types of Quality Control Loops Management level Control loop between levels Planning level Control loop within a level Steering level Control loops in machines Operational level Control loop near machines Page 5 QCL Quality Control Loop The picture shows a four-step company model, which demonstrates simultaneously the intra-corporate information-model and the Quality Control Loops in companies. - Management level: Defines corporate targets and derives company concepts - Planning level: Concepts are transformed in job instructions for execution (e.g. progress planning) - Steering level: Production orders are managed - Operative level: Concepts and strategies are transformed in real products In all loops, in a level and between levels, the pyramid of knowledge can be found. Within a level, the transformation of information happens within the specific fields of duty. Between levels, e.g. the whole company, the transformation of knowledge is based on the strategic aims of the company. E.g. the management level derives strategic procedures from the knowledge of the processes. Quality and Information L 11 Page 5

7 Benefits of Quality Control Loops Management Level Planning Level Steering Level - Information about the quality levels in the company - Rationalisation with quality aspects - Quality supported investment planning Preventive maintenance - Procurement of machines - Product and production planning with focus on quality Technical and economical selection of suppliers - Assurance of data quality - Clarity of quality costs -... Quality Data Base Operative Level - Reduction of rejects - Reduction of processing times -... Page 6 The advantage of Quality Control Loops at the different company levels can be described as followed: At the management level information about the quality ability of the company enable a rationalisation with quality aspects. The planning level gets information about preventive maintenance, production planning etc. Assurance of the data quality or transparency of quality related costs are relevant for the steering level. The reduction of rejects and processing times are examples for the advantages of the Quality Control Loops for the operative level. The information which are generated in the different levels establish the Quality Data Base. The information can be changed into knowledge through the combination of context and experience (pragmatics). Actions can be derived from the knowledge. Quality and Information L 11 Page 6

8 Model of a Quality Control Loop Disturbance variable + Controlled system Process and Product Control variable 7M - Manipulated variable Process intervention Analysis of tolerance Change of construction Controller On-Line- Controller Off-Line- Controller + Target value - Quality Data Base Page 7 Model and Systematic of a Quality Control Loop To illustrate the mode of operation of Quality Control Loops the basics of classical control loops will be used. The aim of a regulation is to retain specific parameters on predetermined set points. In technical practice, these parameters are mostly output variables of technical processes. Parameters that have to be regulated, should follow the change of set points as well as possible. Process-operating failures should not have any influence on the regulated parameters. The principle of a system of Quality Control Loops is shown in the picture. By comparing flow technology design with quality assurance, it becomes clear that, in general, the model of flow technology design is transmittable to quality assurance. Quality Management separates on-line and off-line regulators. While on-line regulators are attached closely to the production line (e.g. short-run error-logging), off-line regulators are utilised in indirect sectors (e.g. supported by QFD, FMEA). In the picture disturbance variables are displayed as Ishikawa-diagram (fishbone diagram). They act unplanned on the controlled system. The disturbance variables are symbolically characterised as the 7M of Quality Management (mankind, material, machine, marginal conditions, measurability, management and method). The company-wide integration of quality assuring methods (On- and Off-Line) in Quality Control Loops allows the efficient and fast reaction on incidents in the company. Functional departments and processes can be defined as control paths of Quality Control Loops in the company. Thereby, it is a matter of the whole department, e.g. the construction or production, but also of several production areas such as preparation of a task schedule, drawing or production of a feature of a machine. Regulators do not take effect on these control paths with simple regulation mechanisms, but with methods of the preventive Quality Management. The number of possible regulation parameters rises with the span of the Quality Control Loop. The output of the Quality Control Loop, the disturbance variable, the controlled system and the controller will be integrated in the quality data bases. The classical control loop model has to be extended by an additional component, the Quality Data Base. Quality and Information L 11 Page 7

9 Example For a Machine-Oriented Quality Control Loop Serigraphy Galvanisation Take a sample SPC Check Current Voltage... Turn off causes (correct setting parameter of electroplating bath) Analysis of control chart Identification of disturbance Detection of causes X-Karte S-Karte Page 8 In machine-based Quality Control Loops, the target variable is not identified until the product has already left the process. The results of a test or the occurrence of certain events then trigger the introduction of process-improving measures. Since it is frequently impossible to describe the correlation between target and manipulated variable unambiguously, the control process demands a considerable level of knowledge about the process and is usually conducted by experienced specialists. Approaches to automating control loops of this nature, for example, rely on the use of expert systems. SPC (Statistical Process Control), is an example of machine-based Quality Control Loops. The process of electroplating heated rear car windows is an example of this type of control loop. In a process which has been very much simplified, the mask for the heating wires is applied to the window in a screen printing operation, after which the window is electroplated. After the electroplating bath, samples are taken and the electrical resistance of the heating wires in the windows to be tested are measured. The average control card parameter x and the scatter or range R are then calculated on the basis of the measured values. The progression of the mean values (x) and ranges (R) provides the machine operators with clues to the possible influence of disturbance variables when they analyse the card. When disturbances are discovered, the process is stopped and the cause of the disturbance is determined. In the example outlined above, the settings for the electroplating bath had to be corrected due to a disturbance at time t1, and to the resultant exceeding of the upper action limit of the x value. To return the process to a stable state, the cause parameter (e.g. current intensity or voltage) should be reset. The adjustment is effected within the permissible manufacturing tolerances, ensuring that no rejects are produced, despite the fact that one of the intervention boundaries of the mean value was exceeded. If a control card is to be kept, considerable knowledge about process correlations is required in order to be able to react appropriately when disturbances occur. Therefore, it is advisable to document causes and measures in an appropriate form so that reactions are possible, when new disturbances occur in the future. It is particularly important to file this information so that it can be recalled swiftly and used by higher-level units. Quality and Information L 11 Page 8

10 Imaginary Model of a Quality Data Base Product data Data about manufacturing equipment Production data - Product Data - Characteristics of construction - Process plan data -... Machine data - Tool data - Device data -... Master data - Defect mode - Main plans -... Inspection station data - Inspection device data -... Quality data History data - Inspection data - Defect data - Quality characteristics -... Machine capability - Testing tool history data - Maintenance data -... Process data Production data - Cost centre data - Process data -... Sampling system - Defect catalogue - Causes - Results - Measures Process capability - Defects / Malfunction - Correction measures -... Page 9 The Quality Data Base The data base is divided in product data, maintenance equipment data and process data. Within these three sectors, production data, master data and history data are separated. Production data e.g. are characteristics of construction, machine data and production data. The Quality Data Base consists of a master data and a history data fraction. Master data are desired attributes whereas history data are measured actual values. The Quality Data Base can physically be realised by splitting into several data bases. Quality and Information L 11 Page 9

11 Contents Pyramid of Knowledge Quality Control Loops CAQ - Computer Aided Quality Management Introduction of CAQ Systems Page 10 Quality and Information L 11 Page 10

12 EDP Electronic Data Processing - Systems in Companies Financial management Material management Customer management EDP -Enterprise Resource Planning (ERP) -Operating Data System(ODS) -Material Data System (MDS) -Computer Aided (CAx) Human resource management Project management Quality management Production management Page 11 CAQ Systems 1. EDP-Systems in Companies In companies different EDP-systems are used to support various demands in the different domains of a company. The following domains are being considered: - Financial management - Customer management - Project management - Production management - Personal management - Material management - Quality Management (QM) A so called CAQ-system (Computer Aided Quality) is used in the QM. Quality and Information L 11 Page 11

13 Computer Aided Quality Management CAD BDE/ MDE CNC PPC CAP Statistics Inspection order Test data Evaluation Machine data Quality data Production release Control draft Quality control plan Master data Component draw. Management level Planning level CAQ Control level QM-policy QM-strategy QM-aims Quality planning Quality controlling Testing control analysis of measured values NC-programs Operative level Quality Data Base Acquisition of measured values PPS: Production Planning and Control CAD: Computer Aided Design CAP: Computer Aided Planning ODS: Operating Data System MDS: Material Data System CNC: Computer Numerical Control Page CAQ Computer Aided Quality Management A company organisation consists of many networked control loops which are inside the company organisation structure and the process organisation. The more complex the business processes in the company are, the more CAQ-systems are depended on the integration of other EDP-systems. The picture shows the interfaces to other information and communication systems, as well as the data exchange between the systems. Quality and Information L 11 Page 12

14 Development of CAQ CA CA CA CA Q (P) Q (P) Q(S) Q (P) Q(S) Q (P) Q(S) Q(M) Q(M) Q(O) Result-oriented Function-oriented Process-oriented I = Inspection S = Security M = Management O = Organisation Computer added tasks of quality and testing Single computer-aided measures of quality assurance Integration of functions in planning and production, exchange with internal information systems Company-wide CIMconcept: e.g. Aachener QM-Model, continuously computeraided process of improvement Page 13 CAQ has developed from the result-oriented to the function-oriented right up to the process-oriented view. Out of a simple single computer aided measure of quality assurance became a company-wide CIM-concept (Computer Integrated Manufacturing) for a computer aided continuous improvement process. Quality and Information L 11 Page 13

15 CAQ Function Model Quality planning Quality Function Deployment (QFD) Failure Mode and Effects Analysis (FMEA) Design of Experiments (DOE) Gauge Management (PMM) Quality Quality control Quality Data analysis (QDA) Quality based costs Q-Audit Complaint management IT-requirements and conditions Data transfer Data storage Data processing Internet Third-party system (machines, measuring device, Software) Inspection plan Test data acquisition Test data analysis Test data documentation SPC (Statistical Process Control) Organisational requirements & conditions Inform, control, adjust User administration Distribution of rights Page 14 CAQ- Function Model The CAQ-function model consists of quality planning, IT-requirements and conditions, quality control, quality and organisation requirements and conditions. Quality and Information L 11 Page 14

16 Example For a CAQ System CAQ = QSYS PMM PMM Gauge Gauge Management Management WA WA Finished Finished parts parts SPC SPC Statistic Statistic Process Process Control Control APQP APQP Advanced Advanced Product Product Quality Quality Planning Planning PPL PPL Inspection Inspection Planning Planning FMEA FMEA Failure Failure Mode Mode and and Effects Effects Analysis Analysis Netcom Netcom Master Master data data and and orders orders from from ASCII ASCII file file or or outside-database outside-database WE WE Incoming Incoming EMPB EMPB Green Green Model Model Inspection Inspection Protocol Protocol Data based CAQ-System Main Main User User administration administration master master data data RQMS RQMS Reclamation Reclamation and and Quality Quality Cost Cost Management Management Toolcom Toolcom Loading Loading information information and and data data from from ASCII ASCII files files ( ( protocol protocol files) files) Page 15 Quality and Information L 11 Page 15

17 Process-Oriented Quality Management in CAQ Product Data Management Audit Management Complaint management/cip Inspection tool management Lot persecution DOE Customer to innovation Idea to technology Idea to product Process planning Demand on stock Order to cash Product in use Product Life Cycle QFD Design- FMEA Test planning Control station SPCcheck Incoming Finished part Product- FMEA Process- FMEA Initial sample Distributor appraisal Servicetransaction APQP APQP Quality Initial sample Page 16 The picture demonstrates how modules of a CAQ-system can be integrated in the value adding chain. Single modules are continuously used, e.g. Product Data Management and Audit Management. Others are only implemented in special areas of the value adding chain, e.g. test planning and SPC. This depends on the process of each company as well as on their requirements and demands. Quality and Information L 11 Page 16

18 Computer Aid in Quality Management Example Inspection Plan Inspection tools Inspection plan Inspection plans Inspection data Inspection planning guideline Standards specifications Measuring program Inspection planning Inspection Inspection data processing in order to: - Dynamises the scope of - Identify critical points Inspection data processing of simple-item and smallbatch production: - ABC evaluation analysis - Failure analysis Inspection data management Steps of data processing: - Processing - Setting up codes - Recording - Describing Inspection data processing of large-batch production: - Control charts - Examination of process capability Inspection data processing Page Example Inspection Plan The implementation is oriented on the demands of the planning. The results, which are based on the implementation are documented in records like actual value tables, measured value logs or documentation of failures. The duty of the data analysis is the rating and aggregation of the results to conclusions. These are on one hand communicated as a decision guidance for the planning to update the effort and on the other hand it is communicated to the quality control to initiate qualityimproving efforts. The drive to rationalise in quality testing and is aimed at ensuring, that individual tasks in various areas of activity are performed more effectively (as a result of the automation of individual machining steps, for example ). Furthermore a continuous IT-related communication between the various areas should be ensured. There is evidence that the trend in testing is shifting away from acceptance tests towards in-process monitoring. As a result of the shift in emphasis towards on-going production, failures in the development can be detected and solved more swiftly. The objective is controlled manufacturing which, ideally, would help not producing any more rejects at all. Quality and Information L 11 Page 17

19 Functions of the Inspection Plan Generation 1. Definiton of the head data in the plan 2. Selection of an characteristic 3. Specification of time of 4. Specification of the degree of 5. Specification of the place of PPL?Skip lot? 12. Generating graphics 6. Specification of personnel for 11. Specification of inspect. data processing 10. Specification of documentation of 9. Specification of text of inspect. PPL Text Text Text Text Text Text 8. Specification of kind of attributiv variabel 7. Selection of tool Page Functions of the Inspection Plan Generation For the generation of an plan e.g. tools and characteristics are required. The modules which are regarded in the plan should also be defined (e.g. finished parts, incoming, SPC...). The order to execute the planning functions depends on the size of the company, organisational structure etc., but the determination of the criteria is required for further actions. The guideline recommends that the following list of questions should be answered systematically for each selected test characteristic: - what : Selection of test features - when : Determination of time of planning - how : Determination of manner - how much : Determination of test range - where/who : Determination of test location/personnel - with what : Selection of tools Determination of text Determination of documentation Determination of data processing Quality and Information L 11 Page 18

20 Inspection Planning As an Example of CAQ = QSYS Input Input to to generate generate plans: plans: Product Product Inspection Inspection tool tool Characteristic Characteristic Defect Defect Inspection planning Inspection plan (IP) - Generate - Edit for modules: - WE - WA - SPC - EMPB - Inspection station assigning IP - Save Product IP - Product nr. - Prod. designation -Rooting nr. Group IP: - IP nr. - IP designation Special IP: - IP nr. - IP designation Inspection step - Paste - Edit - Delete Inspection step defining as: - Variable, - Attributive, - Visual characteristic Accept defined step WA WE SPC EMPB - Generating order - Acquisition - Generating order - Acquisition - Generating order - Acquisition - Generating order - Acquisition Page 19 A further objective which is aimed with the use of computers in test planning, is to record, evaluate and use quality-determining data systematically in order to ensure product and process quality and reduce time and costs. Test planning is one of the basic elements of any CAQ system. It is one of the classical CAQ functions, alongside test control, test data collection and test data evaluation. The function of the test planning module is to provide the planner with as much support as possible in the individual machining steps, as well as ensuring a clearly structured approach, all information must be easily and swiftly available. Quality and Information L 11 Page 19

21 Functions of the CAQ Supported Generation of Test Data Choose insp. order Identification of inspector Choose insp. characteristic n.i.o.-output: decision about further utilization generation of test data Transfer and display test data n.i.o.-output: detect type of error and reason n.i.o.: not in order Calculate values of assembled characteristics x f = Σ s Correct test data 12,5 13 Page 20 The recorded test data are stored and processed by the CAQ system. They can be compressed and evaluated on the basis of many different criteria by using statistical techniques. The test data can be evaluated, for example, in an order-, batch-, part- or characteristic-oriented operation encompassing various suppliers, machines and periods of time (e.g. shift evaluations). Evaluations typically supported by CAQ systems, include linear diagrams of the measured values (original value cards) frequency distributions (histograms), statistical characteristic values (mean values, standard deviations, etc.), information about rejects and rework, failure and control charts and distribution tests. Quality and Information L 11 Page 20

22 Examples for Computer Aid Test planning: Generation of test data (variable characteristics): Article plan (=single plan); Article specifical plan based on article number, which is being loaded of the article master data with maintenance sequence Page 21 - Inspection planning - Inspection-data acquisition (variable criteria) Quality and Information L 11 Page 21

23 Example - FMEA Page Further Examples for Computer Aid Example FMEA Quality and Information L 11 Page 22

24 Example House of Quality Page 23 Example QFD Quality and Information L 11 Page 23

25 Contents Pyramid of Knowledge Quality Control Loops CAQ - Computer Aided Quality Management Introduction of CAQ Systems Page 24 Quality and Information L 11 Page 24

26 CAQ Iceberg Training Needs Investment CAQ Support Complexity Availability of new modules Company growth Time for implementation Interface support Internal IT-Support Reliability Language options Acceptability Product Page Introduction of a CAQ-System The following points must be regarded during the introduction of a CAQ-system: - detailed and step-by-step planning of the recommendations - definition of the interfaces to other IT-systems, machines, measurement equipment and divisions - illustration of the manual sequences of the QM organisation in the CAQ-system - qualification of the employees - continuous enhancement of the QM-process and CAQ-system The aim of the introduction is to bring the system step-by-step in further-reaching areas of the company, increasing the effectiveness and the efficiency of the CAQ application continuously. Quality and Information L 11 Page 25

27 Failures During the CAQ-Introduction Missing cost benefit analysis Inefficient project processing High system complexity Failure by interpretation of standards" Lack of project management Failed optimising Wrong economising by implementation No testing of the processes Lack of teaching the users System changing instead of optimising Wrong philosophy Page 26 The failures of the software-system introduction mainly are missing cost benefit analysis and inefficient project processing. Quality and Information L 11 Page 26

28 Stepwise Procedure When Choosing a CAQ-Software Input Start Prozessschritt Output Step 1: Process analysis Input Prozessschritt Output Input Abfrage Abfrage Output Input Prozessschritt Ende Subprozess Output Step 2: Interface analysis Qualitätsplanung Qualitätslenkung Step 3: Target concept ,00 Euro ,00 Euro ,00 Euro Qualitätsprüfung ,00 Euro ,00 Euro 1 Jahr 5 Jahre 10 Jahre Informationstechnische Voraussetzungen Organisatorische Voraussetzungen Step 4: Market analysis/ software selection ,00 Euro ,00 Euro 0,00 Euro Anbieter 1 Anbieter 2 Anbieter 3 Anbieter 4 Messsysteme CAQ CAQ-System Step 5: Integration PPS-System BDE-System Datenbank Page 27 In the first step the process analysis is used to create a company specific process map. Therefore the main processes must be identified. Afterwards, the main processes will be reduced to sub processes. These sub processes can be subdivided in the following steps and input and output information can be identified. In the second step the interfaces between hardware and software components as well as the interfaces between the employees and the divisions are identified using the input and output information of the main and sub processes. This is important for being able to realise the information flow to the right division at the right time. The target concept (step 3) defines the user demands of handling the system. It also describes visions and strategies for the future. Further visions and strategies are defined in the target concept. The current status and the target concept are documented in a requirement specification. Quality and Information L 11 Page 27

29 Explanation of the Stepwise Procedure step 1: Process analysis step 2: Interface analysis step 3: Target concept Company specific processes (actual state analysis) Requirements and visions Specification (requirement) step4: Market analysis/ software selection Decision for supplier step 5: Integration Page 28 With the specification (requirement) and market analysis (step 4) a CAQ software can be selected which is able to show the process map of the company. First, a wide selection is made with a critical catalogue. After that, the different suppliers can be analysed by their module and system properties. Through correlation between the supplier and the processes on the basis of the module and system properties a close-pitch selection is made. In workshops with the selected suppliers, the supplier who is able to show the best process map will be chosen. The integration is the fifth and last step, which must be executed in close co-operation with the supplier, because he has got the knowledge from further projects about how much time is needed to integrate all interfaces. Quality and Information L 11 Page 28