Cell studies in production procedures paper



This paper will generally provide a case study where cell designs of the methodological aspects for the transformation of the production procedures are applied. In this case study, the cell redesign will tightly focus in reaching the material flows optimization levels under the real manufacturing conditions. Consequently, individual techniques were combined together into various compact methodical processes for the purposes of building one-piece flow production. Additionally, the case study was resolute on the relatively typical transformation situation from the batch to cellular manufacturing.

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Executive Summary


Cell formation entails machine populations, analyzing parts, grouping different parts with parallel design features into families and establishing corresponding equipment into cells. In the technological field, various works have been conducted in relation to this field and various clustering algorithms have been put into practice. With reference to the manufacturing cell formation aspect, one of the easiest approaches to this concept is the aspect called ocular. This approach generally examines data classifications by the use of the human eye (Irani, 1999). In most cases, this type of approach entirely depends on the experiences and knowledge of a person to establish it. However, this type of approach has various limitations because a person operates it.


Production flow analysis generally groups various parts into families depending on the process plans and the routing sheets. This methodology is sufficiently accurate and quick for any company by the virtue of routing information. Generally, it rearranges shop floor into manufacturing cells that are independent (Irani, 1999). In developing this, most companies either the manual or the computerized methods of development. However, some companies prefer using both types of methodologies. Most recently, agglomerative clustering use such as complete linkage methodologies and single linkage methodologies in the formation of cells have been examined (Irani, 1999).

Generally, this approach entails calculation of process, which has coefficient of similarities between machines parts. Machines pairs that have closer coefficient similarities placed in similar groups after the establishment of a specific algorithm. Coefficients similarities can be a problem hence deciding the appropriate family parts is still a problem (Irani, 1999). The array-based clustering approach is also one of the most common approaches in conducting cell formation. Recent years has seen this cell formation approach receive extensive studies. The most common feature with reference to this type of approach is the fact that the methodology consecutively rearranges rows and columns of machine matrix depending on the type of index. This aspect is done until irregular blocks or the crosses diagonal blocks become generated. This type of, the approach is always easy to establish and conduct. However, the results of the approach always vary depending with the algorithm type.




Cellular manufacturing remains as a recognized technological innovation in batch production type or the job-shop production to attain economic upper hand, which is similar to mass production.  In conducting the cellular manufacturing systems designs, the company must first establish the operational and structural issues before going on with the process (Irani, 1999).

. The most common challenge and problem that a company seeking to engage in cellular manufacturing will encounter is the selection and grouping of parts, which have similar features and characters into the family (Pycraft, 2000). The entire process is known as cell formation. Over the past years, many academicians and practitioners have found remarkable interest in such problem type. Alternatively, various analytical methods and heuristic methodologies have been established despite the little efforts put in place in the selection of appropriate methodologies. Establishing different approaches such as the clustering approach may end up producing different results some of which might be conflicting especially when the performance criteria are established. In most cases, it might lead to major concerns some of which end up measuring and clustering the company techniques (Pycraft, 2000).


The following research will generally deal with the theoretical background of one-piece concept application by the principles of the (P-Q) Product/Quantity production and analysis of the flow analysis. In bicycle manufacturing companies, the research methodology of the Product/quantity production and analysis of the flow analysis is usually applied.  Generally, most companies change their manufacturing process structures because of various reasons. However, the main reason for their motivation is that the process type layout does not suit them. In most cases, planning oriented production system results to the type of system, which requires pushing for sales (Pycraft, 2000). In this case, the company pushes their own outputs to retailers while the retailers will return what they fail to sell. The returned products will then end up as dead inventories.

The one-piece production concept generally differs from some of the mentioned systems. More differently is the fact that this type of system outputs its products depending on the assembly processes needs. In this case, the output of the system tends to be the closest processes to both the customer and the markets. Products will be allowed for the shipment process only if more products are attained from the manufacturing department.


Conceptual Framework


The importance of material flow optimization aspect is to assist planners to fulfill the needs of their customers in a shortened manufacturing period (Pycraft, 2000). Material flow optimization generally falls into flow management production or management of logistics, which mostly includes raw materials movements, finished goods in a warehouse or within a plant or work in process. In most cases, material flow implementation takes place in the following phases;

In form of a discrete flow and in this case, the material flow implementation is typically for batch productivity (Irani, 1999).

  • Generally, this entire category entails manufacturing of medium-sized lots of similar products or items. Production of lots in this case is done only once or in regular intervals.
  • The continuous materials flow is usually applied in food industries and chemical manufacturing industries. The term also refers to manufacturing of assembled products or single parts.

The main role of cell formation is to convert discrete material flows into material flows, which are continuous with the aim of changing planning-centered productivity on the one-piece production. Implementation of the one-piece flow can be achievable if the organization manages to obtain work progress inventory reductions. In most cases, inventory reduction is achievable when the parts cannot be stored in unit loads or containers at operations while the company is still processing them (Pycraft, 2000). However, the process takes place on one piece at a ago. In this case, the processed one piece and cells will transit between operations. Alternatively, this happens when the parts are established just the way they are ordered. Lots of parts or batches are not always staged between different operations waiting for scheduling.


The Zero-defect production effect is also one of the vantages of this particular concept. In such companies, this aspect is achieved by the creation of the mistake-proofing devices and altering them into production line. In as much as the one-piece flow production concept seems to have been introduced lately, the concept plays a significant role especially in the modern and dynamic manufacturing environment (Pycraft, 2000). One-piece production has various theories generally. One of the most common theories in relation to this concept is the Production Flow Analysis theory, which deals with planning Group Technology. Most analysis usually focuses on some of the basic principles that pertain the process flow building. In line with this aspect, many industries are designed in such a either way that they have unique one-piece flow systems U-shaped floor plans, L-shaped or parallel in order to obtain their needs (Irani, 1999).

Generally, the basic conditions that pertains the establishment of one-piece flow systems are;

  • Create the factory layout conducive especially to its overall production flow.
  • In this case, the factory must at least include pathways, which are clear.
  • There should always be a clear distinction between product output and material input.
  • The production line must always have a consistent single operator that is U shaped.
  • Thorough layout inspection is always advised
  • Alternatively, there should be minimal in-process inventory.


From the context, it is quite evident that small workpieces are never ideal for the production of one-piece because they tend to produce too much waste during the setup positioning. Alternatively, small workpiece concept is not appropriate in a situation when the changeover times become long.


Problem and Methodologies used in the framework


In this case, the manufacturing company engages itself in the manufacturing of bicycles components and the components tend to differ in terms of their sizes and shapes. From the viewpoint of production, this particular category entails manufacturing of medium-sized products or Lots items, which are similar. In this production, lots of production of lots is done only once or on regular intervals (Pycraft, 2000). In some cases, production of lots is done on regular intervals or on lesser occurrences. Consequently, the machine for the manufacturing equipment in this particular case study was designed in such a way that they are able to produce high rates (Irani, 1999). Alternatively, the machine tools are mostly combined with fixtures and designed jigs, which play an important role in increasing the output rates. Production flexibility in such manufacturing companies is ensured by putting in place the semi-automatic machines for production. The manufacturing company always aims most of its activities towards increasing its production volumes by innovating most of its production facilities and the development of methodological management (Pycraft, 2000).


Limitations of using the direct clustering analysis


Using the direct clustering analysis has always gone through a lot of criticism by many practitioners.  The research study indicates that the data results of BEA have the ability to cluster. In doing this, they will be inputting matrix into four different groups with the aspect of exceptional elements (Pycraft, 2000). In as much as there are exceptional cells after the process, there is the possibility of a lower grouping efficiency while machine utilization will be lower as thought. Alternatively, the total bond energy would be less. This will mean that the DCA algorithm will have various deficiencies, which might end not working effectively for some of the input matrices.

Competitive aspect

Generally, bond analysis of this methodology in cell formation manufacturing remains the best among the other methodologies tested. Comparing the results of the two methodologies, the P-Q analysis process tends to be more favorable.  Alternatively, BEA has the ability to compete with some of the most complicated methodologies in reference to cell formation manufacturing. In as much as data sets show BEA results being in lower grouping efficiency and machine utilization, the difference from the results is not substantial (Pycraft, 2000).


Theoretical background for P-Q analysis process


After the determination of the current production situation, the next main aspect towards building operation, which is successful, is the aspect of designing an effective system design. In this case, a design, which is effective, should at least put into consideration the organizational products, procedures and facilities (Pycraft, 2000). Alternatively, the design should consider the controlling operations, long and short-term goals and the minimum ergonomic requirements of the organization. Systems designs are always important for most organizations. In most cases, they help organizations to define the cost structure of a given product in the organization and determine the organizational position when it comes to the market (Pycraft, 2000).


It is always important to establish a design, which is able to meet some of the present need, and the future needs of the organization (Irani, 1999). Alternatively, the operations in the organization should not be outdated. In establishing this, the organization will ensure that it keeps producing superior products thus enhancing the organization in future especially in the competitive markets. The first and the most important step in establishing an effective system design is the aspect of Product-Quantity analysis (Pycraft, 2000).



Figure 1: Production equipment layout and material flow during processing



The outlined ration in the Product-Quantity analysis diagram shows individual X-es thus a source for production equipment decision-making concepts on layout aspect in the factory. Translation of the figure is done as follows;

  • In case the X1 approaches 80 percent, then establishing small out production line varieties will be reasonable. In this case, there is need for the application of the one-piece flow concept.
  • In case the X2 remains stagnant at 70% value, then the decisions regarding the production equipment layout will totally depend on the manager’s intuition and experience.
  • In a situation where X3 approaches 60 percent, then it would be advisable to organize equipment production in technological patterns because of the relation that exists between manufactured pieces and assortments that are not suitable for one-piece principles implementation procedures.

From the diagram, the interval interest is the area where the source thesis has a marking while X2 value in the Product-Quantity analysis diagram intersects at the point where the Lorence curve is marked which stands at 70% (Pycraft, 2000). To do away with uncertainties during decision-making process, a mathematical algorithm will be used to help in clearing decision parameters (Irani, 1999).




Figure 2: Interest interval


Figure 2 generally demonstrates the difference between the 60 percent margin that the theory defines and the actual amount X3 as a product. Generally, various rules are used to define the not so ambiguous criterions during the decision making process between the product layout and process layout while using the Product-Quality analysis (Pycraft, 2000). The first aspect is opening the 65<X2<70 interval. This aspect was chosen because of its mathematical conditions during its application while making algorithm decisions. From the study, there would be an application and testing of the concrete examples when it comes to the real manufacturing company. These aspects would be presented through the theoretical hypothesis. Additionally, the best method to apply in this case would be the PFA analysis method. In doing this, it will be aiming on the optimization of the flow materials (Irani, 1999).




Figure 3: Multi product process figure


Based on the chart, more production steps in reference to the flow analysis can be used. Generally, every stage in the PFA will eliminate any operational wastes and production flow delays progressively especially in smaller locations of the factory (Pycraft, 2000). Alternatively, PFA entails a comprehensive material flow methodology, manufacturing designs, the aspect of family formation and finally the facility layout design, which was established during the early 1970s (Pycraft, 2000).

From the research study, it is quite evident that clustering results are dependent on the data. Therefore, data selection sets remains an important in this study. Alternatively, testing data can generally be generated from generator numbers, which are random, or from literature. Comparing tested algorithms performances with clustering algorithms, the existing data sets ought to be used.  In this type of research, the results indicate that some data sets remain clustered while some of the data are never affected. In order to ensure that there is a maximum homogeneity and consistency, the sets of data will need to be placed differently from the program and a through access (Irani, 1999).




Presented production process of transformation can generally be viewed as an optimization way of material flows. This will be possible by attaining the organizational logistics goals and altering the production equipment layout. Generally, optimization of material flow belongs to managerial problems and complex engineering that have not been solved to the required standards. From the research, it is obvious that it is a bit challenging to present the complexity of the research (Irani, 1999). Establishing this research study from one angle is important because it helps in the verification of decision-making processes.  It also makes the process more effective especially on the P-Q analysis criteria. Consequently, production of equipment layout transformation of the 6 lines played a key role in the improvement of economic aspects in the organization.


Summary of findings


Generally, the algorithm makes use of simple network architecture. In doing this, it plays a key role in helping the reduction of computational burden unlike the other forms of algorithms. Alternatively, ART 1 limitations depend on the presentation order especially on the network input (Irani, 1999). Performance measures that relate to the resulting cells especially in problems that relate to cell formation generally exists in most part of the research study. Alternatively, the bond analysis of P-Q analysis methodology in cell formation manufacturing remains the best among the other methodologies tested.  Moreover, the array-based clustering approach remains an important approach while conducting cell formation. The most common feature with this type of approach about using the methodology is that it sequentially rearranges both rows and columns of machine matrix depending on the type of index.



DCA – Direct clustering analysis

ROA – Rank order clustering

BEA – Bond energy analysis


Irani, S. A. (1999). Handbook of cellular manufacturing systems. New York [u.a.: Wiley.

Pycraft, M. (2000). Operations management. Cape Town: Pearson Education South Africa.

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