Question

References Summer Version AR. Saved Review View Help Open in Desktop App 12 A Ă B I u Tell me what you want to do ON AVAO Editing E Styles O Find Q4. (25 marks) Imagine you are the owner of food manufacturing business and you wish to do quantitative analysis for your company, explain the steps of your analysis? How do you identify the major problems? Header Header GAME Р DAN W DO * ) 3 4 5 6 7 8 9 E E R T Y U 1 0 P

Answer 1

Quantitative analysis is the process of collecting and evaluating measurable and verifiable data such as revenues, market share, and wages in order to understand the behavior and performance of a business. In the past, business owners and company directors relied heavily on their experience and instinct when making decisions. However, with the era of data technology, quantitative analysis is now considered a better approach to making informed decisions.

The proposed integrated approach focused on the quality planning phase of the Juran trilogy, which has been suggested to be the most important stage that can impact the whole product life cycle and customer satisfaction (Juran 1998). Figure 1 shows the functions of the integrated approach with the use of qualitative and quantitative tools. Vector Y represents the critical quality characteristics obtained after QFD I, which was used as an input of quality characteristics for the parameter design during step 4. Vector X represents the critical process parameters that are obtained using an adapted QFD II. This was also used as input during step 4 of the Taguchi parameter design for obtaining optimum operating conditions. Further, process validation and initial quality control based on these quality characteristic was carried out using short‐run SPC. Thus, this methodology suggests a compact and integrated use of qualitative and quantitative tools that formulate into good data planning and representation. The proposed method was developed and implemented at the Black and White Cookie Company. The data sets and results that were included covered real‐time information from the conceptual stage up to the full‐volume manufacturing phase. The product to be manufactured was a dessert cookie of two variable sizes of 11.4 cm (4.5 in.) and 6.4 cm (2.5 in.), which were oven‐baked with two separate flavored icing of equal halves on top.

1 (QFD I / HOQI) Voice of Customer HOQ 4 2 Process analysis: Cause & Effect Diagram Process Characterization and Optimization 3 X 5 6 (QFDII /HOQII) Adapted process HOQ Statistical analysis Short-Run SPC Initial process Customer focus deployment Optimum operating conditions control before phase out I | Quality Planning

Customer Focus Deployment

QFD is an important tool to capture customers' requirements and expectations. It is such a tool for incorporating the customers' needs and requirements into the product development process (Clausing 1994; Grovers 1996; Vonderembse and Raghunathan 1997; Besterfield 2001). However, the application of QFD for the development of food products has not been given enough attention. The QFD technique as it is used in other industries should be modified to meet the development of an improved food product. It has to be understood that in food products, the final quality of the product is dependent not only on the quality of the ingredients but also on the food production processes. To keep the QFD matrices manageable, simplifications were made to the product (Xie et al. 2003) using an adapted House of Quality (HOQ) matrix with related technical objectives in the “WHATs” rows and product/process parameters in “HOWs” columns.

Since the selection of important quality characteristics was strongly influenced by customer needs, the QFD I or the HOQ I matrix was first developed to integrate customers' desires and tastes into the design. It was important to keep the QFD matrix manageable for manufacturing process development. The approach procedure adopted in this case is described as follows:

• 1

  Identified the customer segment with knowledge of the specific product in the market, gathered customer needs (WHATs) using questionnaires from customers, customer needs were organized into a hierarchy of primary and secondary needs using affinity diagram and the importance of each needs were based on the ratings of customers.

• 2

  The QFD team at the organization would consist of a cross‐functional team of product development engineers, food specialists, management personnel and facility operators. This team came up with the (HOWs) technical characteristics or process parameters that made the outline of HOQ.

• 3

  The relationship matrix was filled by the QFD team to define the relationship strengths between the HOWs and the WHATs by assigning weights. Absolute weights were calculated for each quality characteristic at the bottom of the matrix.

• 4

  The top 25% of the quality characteristics with highest ratings were chosen to be the critical quality characteristics.

In QFD II or HOQ II, a process breakdown analysis method and a cause‐and‐effect diagram were used in targeting the exact process concerning the critical quality parameters that had been established by the QFD I process. The chart gives a good visibility of the whole brainstorming process, which can be used beyond the planning phase to the improvement process based on organizational discretion (Besterfield 2001).

Process Characterization and Optimization

Investing more efforts in design stage can enhance design quality into a product. Later, this will reduce of the need to rely on inspection for quality insurance. The identification of the critical process parameters and its optimal settings will result in increased customer satisfaction and low defect rate in the hands of customers (Antony et al. 2006). This task can be accomplished by a systematic experimental design (Montgomery 2003). The quality characteristics obtained by QFD I would be the experimental responses, while the important process parameters identified by QFD II would be the design factors. The most often used statistical tools are full or fractional factorial design and can be carried out using analysis of variance (ANOVA). In the case that there are many factors needed to be studied, fractional factorial design was often used in order to reduce the number of experimental runs. Significant factors that affected mean and variability were identified, and optimal conditions were predicted based on statistical results and graphical trends.

Initial Process Control

The benefits that SPC can accrue to manufacturing processes have long been recognized in the engineering‐related industries. These benefits include an accurate assessment of process capability, predictable levels of process control, a timely detection of process drift or causes of variation, a quantifiable customer quality assurance and an effective recording data related to quality. Upgrading the available guidance literature to produce something more specific in the food industry is suggested (Grigg 1998). The planning of monitoring and control of critical processes should be a part of the basic planning phase (Juran 1998). Short‐run SPC focuses strongly on the planning phase to keep the process under control at the infant stage.