Case Study 2- Six Sigma DMAIC to improve inventory management operations

Key Words:

Process Capability, Statistical Process Control, Process sigma level, defects per million opportunities.

Introduction:

In the company "Marco Polo" there have been problems of damage to containers of powdered milk during inventory management operations. Also causing problems with customers due to the delivery of these products. For this company has a defect level that reaches 25,777 defects per million opportunities.

The company has also the idea that it should improve the boarding process and inventory management through the study of the routes of the product. For what could be applied simulation tools and mathematical programming, in function of increasing the productive capacity shipping freight more months. Here is a typical example of one of the main contradictions in business, increase production capacity or increase capacity in terms of quality. . A description of the Six Sigma DMAIC methodology to solve this case.

 

Define

Definition and scope

The first step in this project is to define precisely what constitutes a defect in this case is considered a defect to any damage to the containers of powdered milk that expose content, thus compromising their safety. That is why this project is aimed at improving the operations improved inventory management, storage, sorting and shipping.

Data Quality

The data used in this study were obtained over 16 weeks (96 days) from the accounting records of the company, which were verified through periodic audits and reviews records and processes.

Process Map

Project prioritization matrix

For the selection of possible alternatives for improvement, which have to optimize inventory handling process in the company, used the project prioritization matrix. Possible projects are (as mentioned above) reducing damage to the containers and the route optimization products. As we can see on Table 1 and the resulting graphs 1, 2 and 3. The project with the highest priority is to prevent damage to containers.

I-MR Chart of Damage( %)

For projects that exist in terms of route improvements and elimination of defects by broken packets, economic benefits are expected from 185 to 340 thousand dollars a month. In cases where there are quality problems, it is not recommended (unless you have high demand and little competition in the product market) increasing production generally should increase the quality because if they keep the same level of production costs by failures tend to be higher

Summary of % Damaged

CONCLUSIONS:
• The process of handling of inventory in the company "Marco Polo" has a very high level of defects, which are generally motivated by problems of breakage (conteiners of powdered milk).
• Studies show the process in statistical control but with high levels of defects.
• The main quality problems that present containers are breaks in the corners and bumps.
• To solve these problems a test performed to change the spatial distribution of the work area and reduce the length of the holders of stock handling equipment.
• The proposed measures provide a process in statistical control, with fewer defects.
 (just a sample of the whole study).


CASE 3. Quality improvement of cans for conserved food.

Key words

Suppliers Selection, Process Capability, Statistical Process control, Sigma Level of Process, Defect per Million of Opportunities, DMAIC

Introduction

 

The Factory of metal components ONIX ® develops a wide range of products, including cans are preserved. These cans are used by several customers, which are major producers of foods like meat and fish. In recent weeks there have been many complaints from customers about the quality of the product delivered, for they have detected the appearance in lots of cans with leaks and damage to the other with nicks in the body. Below a description of the Six Sigma DMAIC methodology to solve this case:

 

To Define

 

Upon Receiving these complaints policy ONIX ® appoints a task force to Investigate the causes of defect generation. This equipment is improved with two possible causes of this problem, Which are opposing, as Shown in the Following table:

 

Type of Cause

Action

Possible errors

The damage is caused by a relatively minor wear and tear on machinery

Workers or technicians can reduce or eliminate the problem by adjusting or replacing the affected parts of the equipment.

Mistake 2: Believing that the problem is common (poor quality tinplate) and make adjustments to the machine in a timely manner.

The cans come with defects because management buy lower quality tinplate, perhaps in an effort to reduce costs. What the operator does not even notice, and neither the administration is aware of the injury.

There is nothing that operators can do about the problem. Only the administration can change the purchasing policy.

 

Error 1: when the assembly line can throw a defective natural reaction might lead the operator to adjust the machinery. But the problem is in the material, so that the adjustment can decompose the system and make it worse, leading to new and more serious problems. Meanwhile, the real source of the problem (material) go unnoticed.

 

After this analysis, the improvement team is a question: how to investigate the causes found to know which of the two is to be attacked? To do this you have to decide first check whether the process is stable or if the raw material is adequate cause What should be checked first?

 

To Measure

 

In this case you can check whether the process is stable without having ruled that the raw material is suitable, as in case you will not be introducing a variation due to process, so that the state may be affected control.

Of all the quality features that are required of providers, only this case is important for the hardness, which are performed by analysis of this variable to the tin purchased from each supplier, which must be greater than 90 N / m2. The results of the analysis, applying the Vickers test is shown below in the following table:

 

Supplier 1

Supplier 2

Supplier 3

84,8949

97,697

85,7721

97,7484

87,119

89,4851

83,6844

100,368

89,3418

To Analyze

 

To get a better appreciation of the results of experiments assessing the ability of suppliers, which are shown below. From the analysis of capacity can be deduced that the only supplier able to meet the specifications is number 2, despite having a value of defects per million opportunities far greater than that required for a process operating at Six Sigma (742 defects per million).


Process Capability of Supplier 1Process Capability of Supplier 2Process Capability of Supplier 3


To improve

 

After verifying the lack of quality of the raw material proceeds to verify if the process is in statistical control, for what is beginning to be produced using raw materials provided by the supplier only 2, of this production data continues to be extracted to form A stability study of the process, the extracted data, showing the number of defective units per lot of 10,000 pieces, which can not exceed the limit agreed with clients and 0.5% of defects are presented in the following table.

 

Sample

Defects

1

21

2

24

3

16

 To Control / Check

A study is performed of capacity and stability of the process, where we find that the overall process is stable, despite having two points out of control, and the process is able to meet customer specifications. The 26 defects per batch values ​​are an average of 0.198462% defective. This is equal to 1984.62 defects per million. The confidence levels of 95.0% indicates that the average percentage of defectives in the sample population is not greater than 0.213414.

The Z value of process converts the average percentage of defective capacity index similar to those calculated when assessing the ability of continuous data. In most cases, it is desirable Z value of at least 4, in this case 2.8 is obtained, which indicates to the process to improve quality indices of global class.

The tolerance limits show the likely variability between samples in the population. In this case, 95.0% of all the samples of average size can be expected to have no more than 27.0 defective elements.

Poisson Capability Analysis of Defects

Conclusions.

  • The main problem affecting the quality of the production was given by the difference of quality raw materials that are purchased from the three suppliers.
  •  It is required a system to control raw materials purchased.
  • Commercial relations with Supplier 2 are the only beneficial.
(just a sample of the whole study)

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