Issues of Increased Reliance on Automated Machinery

Literature Review

Nowadays, automated machines and state of the art customized equipment are increasingly replacing work that used to be done by people.  Therefore, with such an increase in equipment automation, manufacturing plants now have many more assets to maintain (Cortes & Morales, 2012).

Moreover, the increase dependency in automation and machine reliability makes production and completion of customers’ orders more vulnerable to equipment downtime, and offering a safe workplace to employees operating such machinery.  Additionally, customizing equipment to a specialization increases the possibility of failures, and the prediction and prevention of such failures are more difficult to be identified (Cortes & Morales, 2012).

On the other hand, many organizations have programs aimed at eliminating waste and incrementing urgency to respond.  For this reason, organizations have adopted systems with low levels of inventory on hand and in the production process, and in case of equipment failure, this has a direct impact on customer service.  Extended equipment downtime in the manufacturing process no longer generates a reduction in inventory on hand (which in principle would pass unnoticed by customers), but generate real time delays in delivering to customers (Cortes & Morales, 2012).

This issue affects the manufacturing industry, and for such reason the use of software tools is essential in keeping track of inventory on hand and their financial cost, but it is limited to the inventory criticality and equipment hierarchy in the manufacturing plant (Rawat, 2015).

In addition to the ease of implementing inventory software tools to reduce downtime and associated costs, the high initial cost of acquiring the software is a hard hit to the finances of small and medium size organizations.  Even then, there is evidence that companies that use the software have struggled to establish the criticality, priority and hierarchy of their inventories.  (Rawat, 2015).

Following on this reasoning, Voltran WEG Group, a company that manufactures power, distribution and specialty transformers, did not have an inventory management software, and used inventory systems with periodic review.  By having a large assortment of products in production for long term distribution in the total inventory, the accuracy of inventory on hand was erroneous (Gutierrez, Panteleeva, Hurtado, and Gonzalez, 2013).

The mentioned periodic review inventory model suggests certain criteria when selecting inventory items like: production quantity, cost, safety, maintenance, suppliers, etc.  Therefore, to apply an ABC arrangement to parts with higher importance is the best way to manage inventory, and this was very suitable to apply and adapt for Voltran WEG Group to manage their inventory.  (Gutierrez et al., 2013).

The company benefited when using this model by learning which products were critical and had a high demand rate, and to determine what could be the optimal levels of service.  Knowing that by reducing inventory on hand costs, the company in turn reduces the total inventory of the plant.  Doing this allows the company to schedule production to complete customer orders on time, and to minimize penalties and fines for non-delivery of their products.  (Gutierrez et al., 2013). Nevertheless, there are different opinions regarding inventory management in a manufacturing plant.  These vary depending on what is to be emphasized as the end goal.  It can be shorter delivery times, highly satisfied customer service, cost of goods, inventory levels, or many other options.  For this reason, for most of the small and medium sized companies it is crucial to implement the best ways to manage their resources.  On the contrary, poorly managing their inventories could result in sale loses and losing important customers (Izar, Ynzunza, Castillo, & Hernandez,2016).

Another example is the method used in a pasta production plant, where a maintenance system was implemented for their equipment in order to optimize the use of raw materials and spare parts damaged by emergency and unplanned production downtime.  (Serrano, 2014). In the absence of a computerized maintenance management program, the company tried to manage using Microsoft Excel.  A list of equipment was generated analyzed for the hierarchy and criticality, so that the equipment could be organized and to develop a list of tasks for the maintenance technicians doing preventive maintenance on the plant assets.  (Serrano, 2014).

Once the conditions of the equipment within the plant were established, it was concluded that creating a plan for equipment maintenance would help in predicting the root causes of equipment downtime.  This is turn would help in structuring a maintenance program, which would help to improve production and to maintain the equipment.  It was also imperative to create a criticality analysis to each of the machines within the plant to determine their level of importance.  (Serrano, 2014)

Additionally, Chen (2011) shows a new method to rank the inventory used by traditional ABC methodology, which is the multiple criteria inventory classification (MCIC), this methodology proposed by Chen in which, based on evaluated criteria and percentages, the performance of each item is evaluated.  When comparing the method used by Chen against other MCIC systems, this new ABC inventory methodology excels as more reasonable and easier to understand.

However, when a more effective proposal is needed to manage small amounts of inventory, the most effective strategy is the slow-moving items in inventory management (Chevreux, 2010).  This strategy was implemented in a manufacturing company with a small amount of parts on their inventory, the system is aimed to stock all critical parts, but in minimal amounts. From the analysis and examples previously mentioned, inventory management in general is highlighted.  In addition, information on this literature review allows to compare the ABC method to others for categorizing inventories.

Conceptual Framework

Inventory

An inventory is the storage of different types of materials that at a determined time are used to meet a demand. The theory of inventories resides in controlling and planning the amount of materials arriving from suppliers and being delivered to consumers.  (as cited in Moya, 1991, p.19).  According to Moya (1991), inventory is defined as the accumulation of material that will be used to meet a future demand.

On the other hand, Heredia (2007) confirms that generally speaking inventory can be defined as the existence of all types of material, unprocessed, items and products, which are used in a production process, and all products or items which are used directly or indirectly in the manufacturing processes or services of a company.

Inventory Management

Inventory management consists of having the best financial situation to control the demand needs on a productive process, but having as an end goal to satisfy the customer’s orders (Gonzalez, Guerra & Montes, 2006).

It can be said that the broad objective of inventory management is to maintain the times in rhythm for supply and demand of any type of material.  (Gonzalez, et al., 2006).

Customer Satisfaction

This is one of the main and most important objectives, as this indicates the quality of service to each individual customer because this helps to relate the expectations and perceptions of each interaction.  (Perez, 2007, p.31)

Theoretical Framework

The topics listed below are contributions from different authors, with the help of their performances provide a significant contribution to the next job.  In addition, different models are shown in the analysis of inventory management, which can be used in industry or research level.

So that companies that are in an operational environment and want to highlight in inventory management.  They can add a contribution to the company and use one of the systems listed below.

Control of inventory on hand

All large companies have some form of planning or inventory management.  The company does not need to be a production company, it may be a blood bank to keep track on the different stock levels, or a financial bank to keep track of their cash on hand.  (Render, 2006).

It is a list that needs to be updated continuously.  It becomes necessary to use software tools and techniques to prevent the use of unnecessary goods on hand and to maintain a trustworthy database without generating out of stock situations.  (Monks, 1997).

ABC Analysis

Parts inventory depends on how machinery is used and maintained.  Inventory management of spare parts is a complex problem that must be analyzed using certain criteria as defined by Jouni, Huiskonen, & Pirttila (2011), who also proposes to review internal factors in inventory management.

According to Cortes and Morales (2012) to classify inventories and to understand how they can be classified, it is necessary to understand the different factors such as buying, costs, supply and demand, among others.  The ABC classification serves as a tool to gain control over these factors using percentages for their final classification.

Other authors differ in the percentage proportion of items A, B and C, such as Wild (1997), who recommends a distribution with the following values:

• Items Class A = 10% of all items, with about 65% of total use.
• Items Class B = 20% of all items, with about 25% of total use.
• Items Class C = 70% of all items, with about 10% of total use.

ABC inventory

To control hundreds of items it becomes necessary to group assets according to their main physical characteristics and level of importance, their cost, suppliers, and maintenance, and this is known as ABC classification, A – extremely important, B – moderately important, and C – relatively unimportant.  The ABC classification then applies to identifying items in the most appropriate way to manage inventories (Kirche & Srivastava, 2005).

Pareto Chart applied to inventory management

In 1907 the economist Vilfredo Pareto (1848-1923) expressed his belief that in Italy 80% of the money was being generated by 20% of the country’s population.  The smaller group was called “vital few” and all other “trivial many.” Eventually this became known as the “80-20 Rule” or Pareto law (Muller, 2004).

As the criteria can generate many measures, it is advisable to group the values ​​of each criterion.  Lung Ng (2007) proposes using a model with several criteria to classify inventory, where this model converts all the criteria measured for an item in inventory to scale value.  This is based on the results of the first ABC without using a linear diagram.

Figure 1.  Behavior percentage of annual items

Source: (Kirche & Srivastava, 2005).

Therefore, in a visual the Pareto chart when applied in ABC analysis to classify inventory is represented on the graph by the Pareto curve where the ratio of the percentage of accumulated parts against the percentage of use is established as shown in Figure 1.

In the case of critical spare parts, limits need to be set to define the ABC classification and the behaviors of those parts when applied to the equipment within the plant (Kirche & Srivastava, 2005).

Cost of missing parts

The factors that involve recurring missing spare parts in the supply room after minimum levels have been set as considered by Pince and Dekker (2011) lies in estimating the costs of production downtime.  The authors propose studies conducted under the method of reliability, which allows the decision to develop systems that approximate the minimum inventory quantities.  Nevertheless, the cost of keeping spare parts in inventory is important when considering an inventory management system.

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References

• Chen, J. X. (2011). Peer-estimation for Multiple Criteria ABC Inventory Classification. Computers and Operations Research, 38(12), 1784-1791. https://doi.org/10.1016/j.cor.2011.02.015
• Chevreux, L. (2010). A Little of Everything Can Go a Long Way. CSCMP Supply Chain. Retrieved from https://www.supplychainquarterly.com/topics/Finance/scq201002stocking/
• Cortes, B. E., & Morales, L. V. (2012). Design of an Inventory Control System for Critical Spare Parts in a Multi-National Manufacturing Company. Universidad del Valle. Available from hdl.handle.net/10893/8981
• Gonzalez, M., Guerra, J. M., & Montes, A. (2006). Gestion de Aprovisionamiento. Madrid, SP: Akal.
• Gutierrez, E., Panteleeva, O. V., Hurtado, M. F., & Gonzales, C. (2013). An Inventory Model Application with Periodic Review for the Manufacture of Distribution Transformers. Ingenieria, Investigacion y Tecnologia, 14(4), 537-551. https://doi.org/10.1016/S1405-7743(13)72264-9
• Heredia, N. L. (2007). Gerencia de Compras la Nueva Estrategia Competitiva. Bogota, CO: Eccoe.
• Izar, J. M., Ynzunza, C. B., Castillo, A., & Hernandez, R. (2016). A comparative Study About the Impact of the Mean and Variance of Lead Time and Demand of the Inventory Cost. Ingenieria, Investigacion y Tecnologia, 12(3), 317-381. https://doi.org/10.1016/j.riit.2016.07.007
• Jouni, P., Huiskonen, J., & Pirttila, T. (2011). Improving overall performance spare parts distribution chain through part categorization: A case study. Int. J. Production Economics, 164-171. Retrieved from http://scinet.dost.gov.ph/union/Downloads/science_019_314332.pdf
• Kirche, E., & Srivastava, R. (2005). An ABC-based cost model with inventory and order level costs: A comparison with TOC. International Journal of Production Research,43(8), 1685-1710. Retrieved from https://login.ezproxy.lib.uwstout.edu/login?url=https://search-proquest-com.ezproxy.lib.uwstout.edu/docview/218654345?accountid=9255
• Lung Ng, W. (2007). A Simple Classifier for Multiple Criteria ABC Analysis. European Journal of Operational Research, 177(1), 344-353. https://doi.org/10.1016/j.ejor.2005.11.018
• Monks, J. G. (1997). Operations Management: Theory and Problems. New York, NY: McGraw.
• Moya, M. J. (1991). Investigacion de Operaciones: Control de Inventario y Teoria de Colas. San Jose, CR: UNED. Retrieved from https://www.tec.ac.cr/publicaciones/investigacion-operaciones-control-inventarios-teoria-colas
• Muller, M. (2004). Essentials of Inventory Management. New York, NY: Amacom.
• Perez, V. C. (2007). Total Quality on Customer Service. Grenada, SP: Ideas Propias.
• Rawat, K. (2015). Today’s inventory management systems: A tool in achieving best practices in indian business. Anusandhanika, 7(1), 128-135. Retrieved from https://login.ezproxy.lib.uwstout.edu/login?url=https://search-proquest-com.ezproxy.lib.uwstout.edu/docview/1914575232?accountid=9255
• Pince, C., & Dekker, R. (2011). An Inventory Model for Slow Moving Items subject to Obsolescence. European Journal of Operational Research, 213(1), 83-95. Retrieved from https://ideas.repec.org/a/eee/ejores/v213y2011i1p83-95.html
• Render, B. (2006). Quantitative Analysis for Management. Boston, MA: Hall.
• Serrano, L. A. (2014). Implantacion de un Sistema de Gestion del Mantenimiento en los Equipos de la Planta Pastificio Chimborazo. ESPOCH. Retrieved from http://dspace.espoch.edu.ec/handle/123456789/3068
• Wild, T. (1997). Best Practice in inventory Management. New York, NY: John Wiley & Sons.