Statistical analysis and evaluation of kombucha beverage production

The purpose of statistical analyses of process accuracy and stability is to obtain and systematically process information about the quality of products in order to improve the technological process and determine the most optimal parameters of its statistical regulation [2]. Statistical analysis of accuracy and stability of technological processes is a set of methods and actions aimed at determining statistical indicators and patterns of changes in these indicators over time [2].

To identify the quality indicators that have the greatest effect on the total quality of finished kombucha beverages [7], the Pareto diagram quality tool was used. The statistical data of the output control were used to construct the diagram, presented in the control sheet, formed at the enterprise HQ KOMBUCHA LLC.

For the purpose of integer data collection, a five-day working week was adopted for the checklist. Selection of batches was carried out in accordance with according to GOST 6887.0-86 «Products of the non-alcoholic industry. Rules of acceptance and sampling». A total of 10,000 liters of products were produced. One batch contains 1,175 bottles of 0.33 liter volume. The number of batches produced in 0.33 liter containers was 26 units [7]. To determine the resistance, the sampling of units was carried out at the manufacturing plant on the day of production.

Figure 1 shows a checklist of integer data compiled in the finished goods department for o ne working week. _____________________________________________________________

Integer data checklist No 1/003-23
Purpose of this checklist: recording of quantitative and qualitative characteristics ofproducts Оbj ect: soft drink kombucha “Classic " Contro 1 p I ace: finished product workshop Data collection period: business week, second quarter 2023
Type of discrepancy	Monday				Tuesday				Wednesday				Thursday				Friday
Test	i	IT	TIT	TV	i	и	in	IV	i	IT	TIT	TV	i	n	in	IV	i	и	HI	IV
Sour flavor				1	II	1		II			1	1	II	1		1	II	II	Г1
Turbidity	1	II	1	II	III	II	II	III					III		II	1	II		11
Sour odor		1			II	1		II			1		II			1	11	II	1
Presence of coarse suspended solids	II	1	1	1	II	1	II	III	1	II	II		Illi	1	II	II	III	1	III	1
Unsaturated colour of the drink			1		II	II					1		II						1
Batches sent for dilution	0	1	0	1	2	1	0	2	0	0	1	0	3	1	0	1	2	1	1	0
Total:																			17

Figure 1 - Integer data checklist

Based on the data presented in the checklist, the stability of the control process was analyzed using the control chart of the number of nonconforming units in the batch (np-chart), as this indicator is an alternative one.

Then, using the data the average line (average number of samples recognized as non-compliant) was calculated using the formula:

np = ^Zi=inp,                        (1)

T - the number of cycles (T=20);

rip - the number of samples recognized as nonconforming based on the results of the i-th control cycle.

Also, the control limits of the map are calculated using formulas (2) and (3):                                    _____________

UCL_np = np + 3- ^ ’ (1 - v) -           (2)

N - the number of samples (N=17).

LCL_np = np-3- Jnp ■ (1 -                (3)

In this case, we obtain the following values:

rip = 0.85 pcs;

UCL_np = 3.57 pcs;

LCL_np = -1.85 pcs.

Based on the checklist data, a map of the number of nonconforming units in the batch is plotted in Figure 2 below.

np-chart

Figure 2 - Control chart of the number of nonconforming units in a batch of finished kombucha (np-chart)

The control chart shows that there are no drop-out points and no trend lines. The process is in a statistically controllable state and can be considered stable.

At the same time, based on the checklist data (Table 1), a Pareto diagram (Fig. 3) was constructed to determine the most weighted parameters from the list of presented parameters. АВС-analysis was used to construct the diagram, in which, according to the rule «20-80%», the working zone of the axis is divided into three equal parts: the zone of greatest influence (A), which is 20% of the total number of parameters, the intermediate zone (B), and the zone of least influence (C).

Table 1 - Input data for Pareto chart construction

Type of discrepancies	Number of nonconforming, pcs.	Total number of discrepancies, units.	Percentage of nonconformin g, %	Cumulative percentage of nonconforming, %
Presence of coarse suspended solids	35	35	31.3	31.3
Haziness	30	65	26.8	58
Sour odor	19	84	17	75
Sour flavor	19	93	17	92
Unsaturated colour of the beverage	9	112	8,0	100
TOTAL:		112	100	100

Pareto chart

Figure 3 - Pareto chart for determining the degree of importance of kombucha quality indicators

Based on the analysis results, we can determine the influence of the causes of nonconforming of zones A, В and C presented on the diagram on the full quality of finished products. As a consequence, the possibility of achieving a greater effect by detecting the parameters that cause the obtained discrepancies, spending a minimum of time, labour and financial resources on minor and insignificant parameters. The analysis results show that the degree of influence of haziness and coarse suspended solids on the quality of the finished drink was about 58%. Thus, reducing the number of losses that occur in the production of the kombucha beverage is possible by settling the degree of influence of the above indicators.

Using the Ishikawa diagram, we determined the reasons for the identified noncompliance of the finished kombucha beverage (Figure 4).

Lack of leadership of process equipment

No possibility to correct errors

Heads of the                1

organization

Inefficient production plan Insufficient quality

Failure of the kombucha production process

Lack of automation

Equipment wear and tear

Low quality raw materials

Questionable supplier

Lack of activity traceability

Error correction capability

Working conditions

Inconsistencies in production

Inaccuracies

In the management of the QMS

Nori-COmplianC^^ with production technology

Ineffective quality policy

Non-compliance with working conditions Inefficient organization Rejection

I of the workplace of finished goods

Incorrect working time ratio

Controller errors

Passing of substandard Foo!l sponge products                            losses of raw materials during processing

Failure to comply

Personnel with storage coitions errors

Figure 4 – Cause-and-effect diagram of the causes of nonconforming in the production of the kombucha beverage

Thus, the presented work shows the course of statistical analysis with the use of simple quality tools, which was made to identify the significant indicators affecting the total product quality, and presents possible ways to regulate their impact.