1 Listening to the Customer, Capable Processes, successful products Quality Function Deployment, contributions of Statistical Engineering and TPM World Conference on Quality and Improvement Session M38 Pablo Albarracín Arcor Group Corporate Quality Manager Arcor Brasil Daniel Firka CEO. Druida Software & Consulting, IAPC Board Member ARCOR GROUP EXPERIENCES
2 Contributions from Statistical Engineering, TPM and Quality Function Deployment AGENDA Arcor, the Company. Statistical Engineering, Core Concepts. General framework: from the Voice Of the Customer to the Voice Of the Process. Application case: Cofler Block.
3 Contributions from Statistical Engineering, TPM and Quality Function Deployment LEARNING OBJECTIVES Understand what is Statistical Engineering. Know how incorporate Statistical Engineering tools into QFD Process See an example of industrial application of the concepts.
4 Contributions from Statistical Engineering, TPM and Quality Function Deployment ARCOR The Company Arcor was founded in 1951 in the city of Arroyito, Córdoba (Argentina), the company has become a leading industrial group that specializes in the manufacture of sugar and chocolate confectionery, cookies and crackers, ice cream and foodstuff. The Arcor Group have industrial operations in five countries, and has become the first world producer of candy and the main exporter of sugar confectionery products in Argentina, Brazil, Chile and Peru.
5 Contributions from Statistical Engineering, TPM and Quality Function Deployment Statistical Engineering, Core Concepts
6 Contributions from Statistical Engineering, TPM and Quality Function Deployment Statistical Engineering, Core Concepts SCIENCE ENGINEERING UNDERSTANDING INDIVIDUAL ENTITIES USAGE / APPLICATIONS SYSTEMS
7 Contributions from Statistical Engineering, TPM and Quality Function Deployment Statistical Engineering, Core Concepts STATISTICAL SCIENCE STATISTICAL ENGINEERING C D M P D I A A C
8 Contributions from Statistical Engineering, TPM and Quality Function Deployment Statistical Engineering, Core Concepts Strategic Level Statistical Thinking Tactic Statistical? Level Engineering Operations Level Statistical Tools
9 General Framework STANDARD CONDITION CAUSES PROCESS VARIABLE CAUSES Comsumer Complains RELEVANT FUNCTIONAL CHARACTERISTICS QUALITY INDICES WITH TARGET Cpk BY CRITICALLITY VARIABLE 2 VARIABLE 1 VARIABLE 3 QFD Processes Processes Comments, suggestions for Improvement On-Line SPC MODEL OF VARIABLES WITH RELEVANT R 2
10 Tools used in Arcor Group today
11 QFD, Cross process in the organization
12 Kano s model satisfaction Fulfillment
13 Steps of QFD Process in Arcor
14 Step 1 - Collection of attributes valued by consumers. Listening to consumers and observing the market NEW PRODUCT ORDER CONSUMER SEGMENTATION MATRIX WHO? DOING? WHEN? WHERE HOW? SECONDARY LEADING Tables market segmentation and consumer needs in the Request for a new product
15 Step 1 - Collection of attributes valued by consumers. Listening to consumers and observing the market Let us now see an example of how it works. From different research techniques, we define for our product Cofler Block a number of features that are relevant to our consumers and differentials over our competition.
16 Step 1 - Collection of attributes valued by consumers. Listening to consumers and observing the market This information, along with target market analysis, leads to segmentation tables: NEW PRODUCT ORDER CONSUMER SEGMENTATION MATRIX WHO? DOING? WHEN? WHERE HOW? LEADING MENS AND WOMES 18 TO 6 YEARS OLD CONSUMER INPULSIVE - CONSUMPTION OF MOMENTUM IN THE PRESENCE OF THE PRODUCT AT THE POINT OF SALE. MAYOR CONSUMPTION IN WINTER. CONSUME WHAT THE FANS ALL YEAR. NO SPECIFIC NO SPECIFIC
17 Step 2 - Define technical specifications VOC Zone Establish design parameters - Qualitative vs. Quantitative. Frequently we detect properties of a product with high value for the consumer, expressed as needs and expectations which are nevertheless difficult to associate with a measurable variable or attribute of the product. Examples: spreadability, creaminess, flavor, soft palate, etc. VOC - VOICE OF CUSTOMERS / CONSUMERS VOICE OF PROCESS - VOP LINE PRODUCT BASICS PERFORMANCE DELIGHTED PROCESS STAGE EQUIPMENT PLANT CUSTOMERS AND CONSUMERS REQUIREMENTS (CR) BASIC CONTROL S PRODUCT S CONDITIONS PARAMETERS VIARIAVEL STANDARTS PROCESS TARGET CURRENT SITUATION VOC - VOP MATRIX 1. ENG PRODUCT CHARACTERISTICS WITH VALUE FOR CUSTOMERS AND CONSUMERS (TE) VALUE ESPECIFICATION cpk TARGET STANDART LEVEL/ cpk REAL QUALITY COMPONENTS RELATIONSHIP NEEDED CONTITION BENCHMARKING RISK IDEAL GAP #DIV/! OK #DIV/! OK #DIV/! OK #DIV/! OK #DIV/! OK #DIV/! OK #DIV/! OK #DIV/! OK #DIV/! OK
18 Listening to clienst, capable processes, successful products. Step 2 - Define technical specifications VOC Zone Establish design parameters - Qualitative vs. Quantitative. Another example: "tougher bite", "bright" or "roasted peanuts flavor" We could hardly specify them without falling into sensory type controls, based on the senses of a group of people, expensive and imprecise. So what we seek are relationships that can explain and predict these specific product qualities. VOC - LA VOZ DEL CLIENTE/CONSUMIDOR LINEA PRODUCTO BINDHLER PLANTA COFLER BOCK COLONIA CAROYA REQUERIMIENTOS DE CLIENTES Y CONSUMIDORES (RC) INOCUIDAD LEGIBILIDAD DE FECHA DE VENCIMIENTO SABOR COINCIDENTE CON EMPAQUE LEGIBILIDAD DE CONTENIDO DE ALERGENOS PRODUCTO BIEN CONSERVADO INTENSIDAD DEL SABOR A CACAO MAS CANTIDAD DE MANI MORDIDA MAS DURA SABOR RESIDUAL A FRUTAS SECAS ASPECTO BRILLO TAMAÑO DEL MANI INTENSIDAD DEL SABOR A MANI TOSTATO INTENSIDAD DEL COLOR FANATICOS DEL CHOCOLATE DIFERENCIALES NOS HACE QUEDAR COMO REYES BASICAS DE PERFORMANCE OBJETIVO DEL PROCESO MATRIZ VOC - VOP 1. AFLATOXINAS FECHADO Y CODIFICACION LEGIBILIDAD DE TEXTOS LEGALES FUERZA DE SELLADO ESTANQUEIDAD AGREGADO DE ESCENCIA C CONCA LICOR - AZUCAR TIEMPO DE CONCADO % DE MANI SLOPE DE TEMPLADO AGREADO DE ESCENCIA FS EN CONCA % SUPERFICIE MANCHADA CALIBRE DE MANI SABOR MANI TOSTADO CONTENIDO DE MANI CENTROS/BORDE VALOR ESPECIFICACIÓN CARACTERISTICAS DEL PRODUCTO VALORADAS POR CLIENTES Y CONSUMIDORES (ET) CERO AUSENCIA < 1 PPM FALTA DE CONTRASTE O DE LEGIBILIDAD < > XX N > XX psi 3,2 Kg - 3,6 Kg XX Kg +- 1,5% 8Hs +- 3% 25% +-1% +-,5,2 Kg -,25 Kg < 3% XX%PASANTE XXmm - XX% RETENIDO XXmm cpk OBJETIVO 1,33 1,5 1,5 1,33 1, ,33 1,33 1,33 1 1,33 1?? 1,33??? < 1%
19 Listening to clienst, capable processes, successful products. Step 2 - Define technical specifications VOC Zone Establish design parameters - Qualitative vs. Quantitative. Statistical Methods Logistic Regression Factorial Experiments
20 Listening to clienst, capable processes, successful products. Step 2 - Define technical specifications VOC Zone Establish design parameters - Qualitative vs. Quantitative. Logistic Regression Studies influence of explanatory variables over occurrence of attributes Applicable in experimental and observational studies.
21 From focus group activities we got as valued qualities of our product: Listening to clients, capable processes, successful products. Step 2 - Define technical specifications VOC Zone Establish design parameters - Qualitative vs. Quantitative. the hardness of the bite the perception of a lot of peanuts the size of peanuts the aroma of peanuts. Hypothesis: the variable % peanut is a characteristic affecting these 4 requirements.
22 Step 3 - Analyze the process VOP Zone Relationship between CTQ and process parameters Now we use the VOP (voice of process) zone of our matrix. LINEA PRODUCTO BINDHLER PLANTA MATRIZ VOC - VOP 1. COFLER BOCK COLONIA CAROYA REQUERIMIENTOS DE CLIENTES Y CONSUMIDORES (RC) CARACTERISTICAS DEL PRODUCTO VALORADAS POR CLIENTES Y CONSUMIDORES (ET) AGREGADO DE ESCENCIA C D LICOR - AZUCAR TIEMPO DE CONCADO % DE MANI SLOPE DE TEMPLADO D CONTENIDO DE MANI VALOR For each stage of the process we list quality components evaluated according to three aspects: Level of standardization of Basic Condition Stability of Control Parameters / Process Variables Stability of Product Variables measured at that stage. VOP - VOZ DEL PROCESO ETAPA DEL PROCESO TEMPLADO, MEZCLADO Y DEPOSITADO DEL CHOCOLATE EQUIPO MEZCLADO DE INGREDIENTES DEPOSITADO EM MOLDES ESTANDARES CONDICION BASICA PARAMETROS DE CONTROL VARIABLE DE PRODUCTO ESTANDARES CONDICION BASICA PARAMETROS DE CONTROL VARIABLE DE PRODUCTO OBJETIVO DEL PROCESO CONDICION ACTUAL AJUSTE DE TORNILLO DOSIFICADOR AJUSTE DEL TORNILLO MEZCLADOR ESPECIFICACIÓN 3,2 Kg - 3,6 Kg XX Kg +- 1,5% 8Hs +- 3% 25% +-1% +-,5 < 1% cpk OBJETIV 1 1 1,33 1,33 1,33 1,33 NIVEL RELACION CON COMPONENTES DE cpk REAL ESTANDAR CALIDAD AJUSTE DE VIBRADOR DE TOLVA VELOCIDAD DEL TORNILLO DOSIFICADOR VELOCIDAD DEL TORNILLO MEZCLADOR TEMPERATURA DEL TORNILLO MEZCLADOR FUNCIONAMIENTO DEL VIBRADOR DE TOLVA,8 5 5, , % DE AGREGADO,6 5 5 SLOPE DE CHOCOLATE TEMPLADO,9 5 TEMPERATURA DE CHOCOLATE AJUSTE Y CALIBRACIÓN DE ROTORES AJUSTE SISTEMA DE CALEFACCIÓN DE TOLVAS AJUSTE Y CALIBRACIÓN DE PLACAS VELOCIDAD DE DEPOSITADORA TEMPERATURA DE DEPOSITADORA, NIVEL DE CHOCOLATE EN TOLVA % DE AGREGADO, PESO TABLETA,75 3 3
23 Step 3 - Analyze the process VOP Zone Relationship between CTQ and process parameters Factorial Experiments Hypothesis Consistency between Data and Hypothesis Experimental Data
24 Step 3 - Analyze the process VOP Zone Relationship between CTQ and process parameters Detection of influencial factors and interactions A BA DA B CB D C CA DC DB % 2% 4% 6% 8% 1% -4, ,165-1,125-1,125 -,625 -,625 -,
25 Step 3 - Analyze the process VOP Zone Relationship between CTQ and process parameters Here is an example for the characteristic % peanut: Through a design of experiment (DOE) we study the impact of different Process Parameters or variables of the semifinished product in peanut %
26 Step 3 - Analyze the process VOP Zone Relationship between CTQ and process parameters Lets review the evaluation of the Level of Standardization: If a component of the process has high impact on a quality characteristic highly valued by consumers, it then requires a level of standardization ensuring a performance within limits which leads to zero defect.
27 Step 4 - Evaluation of performance Current Condition vs. Necessary Condition The matrix has an area of comparison between the current performance and what is needed to meet specifications VOP - VOZ DEL PROCESO PRODUCTO ETAPA DEL PROCESO TEMPLADO, MEZCLADO Y DEPOSITADO DEL CHOCOLATE EQUIPO MEZCLADO DE INGREDIENTES ESTANDARES CONDICION BASICA PARAMETROS DE CONTROL VARIABLE DE PRODUCTO COFLER BOCK OBJETIVO DEL PROCESO CONDICION ACTUAL AJUSTE DE TORNILLO DOSIFICADOR AJUSTE DEL TORNILLO MEZCLADOR AGREGADO DE ESCENCIA C D LICOR - AZUCAR TIEMPO DE CONCADO % DE MANI SLOPE DE TEMPLADO D CONTENIDO DE MANI cpk OBJETIV 1 1 1,33 1,33 1,33 1,33 NIVEL ESTANDAR cpk REAL RELACION CON COMPONENTES DE IDEAL BENCHMARKING RIESGO CONDICION CALIDAD COMPARADA AJUSTE DE VIBRADOR DE TOLVA VELOCIDAD DEL TORNILLO DOSIFICADOR VELOCIDAD DEL TORNILLO MEZCLADOR TEMPERATURA DEL TORNILLO MEZCLADOR FUNCIONAMIENTO DEL VIBRADOR DE TOLVA , % DE AGREGADO, ,33 1 SLOPE DE CHOCOLATE TEMPLADO, TEMPERATURA DE CHOCOLATE CONDICION NECESARIA 8, 14,7 6,7 1, 13, 9,3 8, 22,2 5,6 9, NO OK NO OK NO OK OK OK NO OK OK NO OK NO OK OK The matrix identifies as NOT OK a component whose performance is less than what is required, evaluating the risk arising from the gap, in order to prioritize risk treatment.
28 Step 5 Process Adjustment Improving the level of standardization Whenever we have a NOT OK component, there is a probability of occurrence of defects Different failure modes appear because: standards are not sufficiently robust There is high variability in the processes. QUALITY INDICES WITH TARGET Cpk BY CRITICALLITY On-Line SPC
29 Step 5 Process Adjustment Improving the level of standardization TPM methodology is a powerful tool to strengthen standards and to achieve optimum results while generating a cultural change ensuring its maintenance over time. Some examples that illustrate how to identify weak standards. ESTANDARES CONDICION BASICA CONDICION ACTUAL AJUSTE DE TORNILLO DOSIFICADOR AJUSTE DEL TORNILLO MEZCLADOR NIVEL ESTANDAR cpk REAL RELACION CON COMPONENTES DE IDEAL BENCHMARKING RIESGO CONDICION CALIDAD COMPARADA AJUSTE DE VIBRADOR DE TOLVA , 14,7 6,7 NO OK NO OK NO OK Adjustment and calibration of metering auger Adjustment and calibration vibrator hopper Adjustment and calibration of the mixing screw LEVEL 3 Those are activities that don t reach the required level of standardization because the performance of process depends on proactivity and compliance by the process operator.
30 Step 5 Process Adjustment Improving the level of standardization After achieving a proper level of standardization, we work on controlling variability. CONDICION ACTUAL NIVEL ESTANDAR cpk REAL RELACION CON COMPONENTES DE IDEAL BENCHMARKING RIESGO CONDICION CALIDAD COMPARADA PARAMETROS DE CONTROL VELOCIDAD DEL TORNILLO DOSIFICADOR VELOCIDAD DEL TORNILLO MEZCLADOR TEMPERATURA DEL TORNILLO MEZCLADOR FUNCIONAMIENTO DEL VIBRADOR DE TOLVA , , 13, 12, 8, OK OK NO OK OK The temperature of the mixing screw has lower than expected process capacity, and also has an higth impact on % of peanut.has a risk level in the yellow zone because its impact on three characteristics
31 Step 5 Process Adjustment Improving the level of standardization We analyze the factors that influence the variability of temperature are mixing screw.las hipótesis que se plantean son: variation in the heating water flow changes in opening and closing the intake valve change in opening and closing the outlet valve change in temperature of heating water We conducted an experiment to understand how these variables play in the temperature of the screw Conclusion 1. Into the limits, the water flow is not a factor influencing temperature. 2. Water temperature and percentage of closure of the valve, are real causes of variation.
32 Step 6 - Monitoring and Evaluation Process Building a Quality Index After the Process Adjustment it is necessary to monitor the process Statistical Process Control allow us to monitor and stabilize relevant variables and process parameters Standards are monitored through basic condition audits. With this information we set up the following model
33 Step 6 - Monitoring and Evaluation Process Building a Quality Index The voice of customers and consumers should be considered in developing a metric to assess process quality. Any quality index must meet be sensitive to variations in those customer-valued characteristics. In summary, the number of claims index must be inversely proportional to the Quality Index CI = f (1 / QI)
34 REVIEWING THE LEARNING OBJECTIVES The concept of Statistical Engineering has been explained to understand its impact over industrial improvement programs. An example of application case has been presented in order to get a glimpse of how different tools are used in a synergic way. Understanding of how statistical engineering can be used side by side Total Productive Maintenance methodology.
35 Listening to clients, capable processes, successful products Quality Function Deployment, the contributions of the Statistical Engineering and TPM Thank you Pablo Albarracín: Daniel Firka:
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