**5. Research methodology**

This study was conducted based on both secondary and primary data collected from the primary sources and ordinary data. Preliminary literature review and existing company condition was scanned to formulate the problems and objectives of the study. The data collection process considered defines measure and analyses the data sources. The process set improvement model and then control the research process. The research draws the conclusion of the resulting analysis with.

As shown in **Figure 3**, the research process start at problem formulation and arrives at conclusion and recommendation. The study has been conducted by considering preliminary literature review to develop objectives and problem statement. The study was conducted by considering literature review from different know sources and databases. The literature was reviewed from databases like Scopus

**Figure 3.** *A methodology framework.*

#### *Development of Integrated Lean Six Sigma-Baldrige Framework for Manufacturing Waste… DOI: http://dx.doi.org/10.5772/intechopen.95279*

indexed, web of science listed journals, PUBMED, MEDIN, research gates and DOJ indexed journals. After analyzing and screening literatures, the study found gaps from literature that helped to know the research focus area. Based on the literature review method of data collection and sources were identified. The data was collected through questionnaires, interviews, and field observation. Data sources were used from primary data which was collected by physical field observation, interviews, questioners and company reports from NAS Foods Plc. Responsible and targeted groups were considered under survey on this study. Interview of top managers were made containing 14 interview questions and answer by 1 management and 2 supervisor of the NAS Foods Plc. during the field visiting.

Questioners for employees also conducted to collect data from employees by using questioner to find detail of the problems that NAS Foods Plc. currently facing. The other data source was secondary data which was used to meet the research objectives, reviewing the existing research work of 48 journals, government reports, some reference books & paper related to lean thinking, six sigma, Malcolm Baldrige national quality award programs, strategies, role impacts on manufacturing and food processing industries. The key challenges, potentials and strategies to integrating continuous improvement tolls also considered. The Early search results show that a total of 400 article reports and thesis were found from various textbooks, academic and professional journals. Then read and sort for relevance to the continuous improvement and waste minimization strategy and tools and for their integration. The article would be assessed of methodology, method of measurement and finding results. Finally 48 article, reports and thesis selected are important and related to this study. The research methodology used the continuous quality improvement tool integration to reach its conclusion (Refer to **Figure 3**).

#### **6. Result and discussion**

#### **6.1 Quantitative result**

#### *6.1.1 Bivariate correlation analysis*

Correlation analysis is used to quantify the association between two continuous variables (between an independent and a dependent variable or between two independent variables. Pearson (r) correlation is the most widely used correlation statistic to measure the degree of the relationship between linearly related variables. The correlation value r = 1 indicated that strong negative correlation existence, r = 0.5 negative correlation, r = 0 with no correlation, r = +0.5 with strong correlation and r = +1 is the strong positive correlation (**Figure 4**).

This study showed the respondent result from questioner and it has 4 sections and 25 questions so in order to see the correlations of all indicators it is preferable to make analysis using SPSS. Based on the above principle the study develop the relationships between the waste measurement variance as we see in the next (**Table 3**) in the SPSS output Pearson correlation r (value of statistical test) should close to +1 and the sig (2-tailed) or p-value is less than 0.05 for strong relation. As we see the table below there is strong relation in each relation.

#### *6.1.2 Analysis of awareness of waste measurement*

Waste measures are included seven perspectives in lean typical. In this study it identified each because waste issue is different from process angle and to see further correlation between each viewpoint. Waste minimization is the basic for any

#### **Figure 4.**

*Pareto diagrams of seven wastes)*


#### **Table 3.**

*Bivariate correlation in between waste measurement parameter.*

organization, in this study waste minimization of NAS food plc. The awareness of each respondent comprised (**Table 3**).

When it has been seen the relationship of each variable in waste perspective have strong relation with significance level of 0.01 and the causal Pearson Correlation of variable of excessive transport vs. inappropriate process their value is 0. 579 which show moderate positive relationship and the highest Pearson correlation in waste perspective is between unnecessary inventories vs. waiting their value is 0.920 it mean that waiting in NAS food is highest factor in unnecessary inventory analysis. There is also highest Pearson correlation that the value is greater than 0.9 between inappropriate processing vs. over production and inappropriate process vs. Defect.

#### **6.2 Analysis of Malcolm criteria measurement**

Malcolm measures are included seven criteria in management perspective. In this study it identified each because Excellence issue is diverse from management angle and to see further correlation between each viewpoint. Quality improvement is the basic for any organization (**Table 4**).

When we see the above relationship of each variables in management perspective, they have strong relation with significance level of 0.01 and the causal Pearson *Development of Integrated Lean Six Sigma-Baldrige Framework for Manufacturing Waste… DOI: http://dx.doi.org/10.5772/intechopen.95279*


**Table 4.**

*Bivariate correlation in between Malcolm criteria measurement.*

Correlation of most variable has a strong positive relation and their value is greater than 0.9 whereas the leadership vs. customer and market their value is 0.960 and it has highest value than the others which shows strong positive relationship.

#### **6.3 Analysis of waste minimization tools measurement**

Waste minimization tools measures are included six perspectives in this study. It identified each because waste issue is different from process angle and to see further correlation between each viewpoint. Waste minimization is the basic for any organization; the company does not adopt any particular standardized approach to larger improvement projects (**Table 5**).

When we see the above relationship, each variables in waste minimization tool perspective have strong relation with significance level at 0.01 and 0.05 whereas the causal Pearson Correlation of JIT vs. Six- sigma their value is 0.370 which show negative relationship and the highest Pearson correlation in waste minimization tool perspective is between lean vs. JIT its value is 0.920 which mean that JIT in NAS food is highest factor in Lean analysis.

#### **6.4 Analysis of competitiveness measurement**

Competitiveness measurements are included five perspectives that help evaluation and decision making within organizations that occupy in waste issue. It identified the correlation between quality, price, time, customer satisfaction and environmental views (**Table 6**).

When we see the above relationship of each variables in competitiveness measurement perspective they have strong relation with significance level of 0.01 and the causal Pearson Correlation of most variable has a strong positive relation and their value is greater than 0.9 whereas the time vs. customer satisfaction and


*\*\*Correlation is significant at 0.01 level.*

#### **Table 5.**

*Bivariate correlation in between waste minimization tools.*


*\*\*Correlation is significant at 0.01 level with Person (2-tailed) and list wise N = 100.*

#### **Table 6.**

*Bivariate correlation in between competitiveness measurement.*

environment their value is 0.934 & 0.940 respectively and it has highest value than the others which shows strong positive relationship it mean that time affect the competitiveness of biscuit product in NAS food is highest factor in customer satisfaction and environment analysis.

### **6.5 Analysis on waste level using the 7 lean wastes**

There are certain techniques obtained from previous studies to analyses the seven lean wastes. Among them, the following stages were used.

• **Defining Stage**: The biscuit production process and determination of VA/NVA activities of NAS manufactures varies biscuits' production lines. The production process of line is run fulltime. According to many studies biscuit production and design revealed that the biscuit production process covers the stages of raw material preparation, mixing, forming or molding, baking by oven, cooling and packing [31, 32]. Each process has a certain design and layout *Development of Integrated Lean Six Sigma-Baldrige Framework for Manufacturing Waste… DOI: http://dx.doi.org/10.5772/intechopen.95279*

in order to obtain quality, process capability and good capacity in order to meet the needs of consumers.

• **Measure Stage**: it a Waste Identification stage. During the field observation, the biscuit production process in NAS factory, there were several waste of resources identified i.e. non-standard process, fail on the ground,Crimean machine waste area, Rapper wastage, Packaging scrap product drops, error metal detector detection, broken, oval, overweight or small products, imperfect shape, non-standard water content, malfunction process, and engine breakdown. According to [33] Toyota identifies seven types of waste and they include 1. Overproduction, 2.waiting time, 3. Unnecessary transportation, 4. Excessive or erroneous processing, 5. Excessive inventory, 6. Unnecessary movement and 7. Defective product.to identifies the observed. The results of this identification were illustrated by a value stream mapping diagram, to determine the actual condition of the observed objects in several indicators, including value added and non-value added time. The value of Process Cycle Efficiency (PCE) was calculated to determine the value of Lean application level at NAS. Measuring stage is the process of measuring and identification of waste occurring at every stage of production process. The occurrence of each waste was measured and classified using the approach of 7-waste classification and finally calculated by Pareto analysis [34].

Analysis on the mapping process of the whole series of biscuit production is illustrated by some activities that are classified as non-value-added activities and some value-added activities (**Tables 7** and **8**). Based on the time measure of the VA and NVA activities, the value of Process Cycle Efficiency (PCE) of 49.64% was obtained. The value of PCE is the result of division between Value Added Time and Total Cycle Time.

A company can be considered Lean if the ratio of value-to-waste ratio has reached a minimum of 30%; therefore, if the company is not lean and can be


#### **Table 7.**

*The value added process in the biscuit manufacturing for 3 month.*


**Table 8.**

*Non value added process in the biscuit manufacturing for 3 month.*

categorized as a traditional company [8]. Because of the value of waste ratio is 36.7%.

• **Analysis Stage**: the definition and analysis of this stage is given as Determination of Critical to Quality (CTQ) and CPM value Critical to Quality. CTQ is a standardized or critical measure at every stage of production processes in order to produce quality products that meet the consumers' expectation in accordance with the capabilities of process technology available. Gazperzs [34] suggests that the characteristics of quality that will satisfy customers should first be identified. Here, the quality characteristics considered as critical should be classified and controlled. Each quality characteristic that has been classified should be determined to see whether it can be controlled through material, machines, work processes, and others control. CTQ standardization helps us to set up a maximum tolerance limit and a minimum tolerance limit. The values of USL and LSL are determining the process variation for each classified quality characteristic. They can also be used as signposts for product and process developments. According to the study by Hasan [35] stated that range of USL and LSL values is determined by the value of n sigma, and the Six-sigma approach (DMAIC method) is used as a reference in order to decrease waste or loss (**Table 9**).

As shown in **Figure 5**, the research found the values of six sigma calculation and enter the number defect observed is 5.25, enter the size of the sample are 78 and the defects per million (DPMO) of 67,308, and sigma of 3. This shows that the biscuit production of has a production capability with a failure of 67,308 every 1000,000 productions, or equivalent to 6.73% loss, and this indicates the production process still has a high failure rate. Also the research calculate DPOM, percentage of defect, percentage of yield, process sigma by process sigma calculator with inserting the number of defect observed and opportunities then automatically it calculate give result as we see above in the picture.

• **Improvement Stages:** this is the place where determination of FMEA is to be conducted and analyzed. A number of improvement steps were established at each stage of the existing processes from the preparation of raw materials, mixing, forming, baking, cooling, stacking and packing. Then, this stage tabulation was carried out on FMEA analysis. The FMEA method was used to determine the failure of the process and to analyze and improve the production quality [31, 36] (**Table 10**).
