Defects

2. 1. 2018
Štítky

The lean approach for the elimination of waste, as described by Ohno (1988), is as follows: “All we are doing is looking at the time line, from the moment the customer gives us an order to the point when we collect cash.

The lean approach for the elimination of waste, as described by Ohno (1988), is as follows: “All we are doing is looking at the time line, from the moment the customer gives us an order to the point when we collect cash. And we are reducing that time line by removing the non-value-added wastes” (p. 9). The definition of waste as well as its classification has been approached by various researchers. In general, researchers have commonly included defects and excess processing as some of the more common factors considered as waste (Senaratne & Wijesiri, 2008). Additionally, other factors have been mentioned in specific industries to broaden this classification. For instance, researchers have suggested “a broader definition of waste to include not only material waste, but also waste generated in a construction project such as waiting times, transportation times…” (Hosseini, Nikakhtar, Wong, & Zavichi, 2012, p. 415). The lean approach towards construction adopts both physical and non-physical waste production. On the basis of the existing literature, waste in the context of construction can be classified into eight types, namely defects, overproduction, waiting, not-utilizing talent, transportation, inventory excess, motion waste, and excess processing.

Defects refer to the absence of acceptable quality (Forsberg & Saukkoriipi, 2007). Defects in products are identified by multiple factors. Such factors may include incorrect instruction leading to incorrect use of components, goods created using low quality fixtures, fixing problems caused by insufficient control, low quality components due to rushed production,  and damage due to handling issues (Lacerda, Xambre, & Alvelos, 2015). The defective identification of a product requires it to be rebuilt, which results in waste due to the use of additional resources. Additionally, defect may cause a manufacture higher cost as a waste due to the negative perception of customers. Defective products require the identification of the primary cause leading to the defect (Mezgebe, Asgedom, & Desta, 2013). As a result, a larger size of batch leads to more waste in terms of additional time. The higher demand of time may lead a manufacturer to scrape a batch completely. In addition to the cost of scraping the defective products, multiple related costs may also be caused that may not be obvious but which may lead to more cost than the scraping of the initial product. Such costs include costs related to rework, materials, lead time increase, failure in delivery, lost customers, transport, and setups (Modi & Thakkar, 2014).

There are many reasons that may cause defect in a product. One of the most common cause for defects is the utilization of inaccurate methods for production cause by operations that are not standard, which may result in differences in the operation processes with different operators (Lacerda, Xambre, & Alvelos, 2015). The problem with designing assembling process is another cause of defect. For instance, if operators are not able to align product components correctly, this may result in problem during the assembling process for the product, which may result in product defects. The lack of maintenance of machines and equipment is another cause that may result in product defects.

The defect in a product may be caused by organizational culture as well. For instance, lack of a culture that inspires confidence in product operators may hinder their ability to solve problems. Such operators may continue to work despite the inefficiencies in the product by making the best use of ill-fitting components instead of seeking to solve to issue (Gupta & Jain, 2013). A related problem is that of training, as lack of adequate training may cause operators to imitate others who may not be adequately prepared themselves. An organization, in addition, may have values that may cause defective products. For instance, firms that emphasize the importance of quantity over quality of output may require the operators to work faster and produce maximum amount of output, irrespective of the quality of the products produced.

Researchers have suggested many ways to ensure there are not defect and as a result, lower waste. The lean approach involves automation, which refers to the use of machines capable of detecting non-standard procedures (Ohno, 1988). The use of devices that identify defective products and either emphasize the defect or prevent the product process from continuing are additional approaches for eliminating waste caused by defects.  The adoption of adequate training protocols and standard operations procedures is another method for reducing defect-led waste that many organizations adopt to achieved the product quality standards. Finally, in order to address the problem of defect resulting from lack of efficient organizational culture, organizations may adopt policies that empower teams to acquire problem solving behavior (Gupta & Jain, 2013). The efficient use of human talent can provide an important source for eliminating waste resulting from defective products.


Author: Henri Suissa


Bibliography:

Ben Naylor, J., Naim, M., & Berry, D. (1999). Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain. International Journal Of Production Economics62(1-2), 107-118. http://dx.doi.org/10.1016/s0925-5273(98)00223-0

Bhamu, J., & Singh Sangwan, K. (2014). Lean manufacturing: literature review and research issues. International Journal Of Operations & Production Management34(7), 876-940. http://dx.doi.org/10.1108/ijopm-08-2012-0315

El-Namrouty, K. (2013). Seven Wastes Elimination Targeted by Lean Manufacturing Case Study ″Gaza Strip Manufacturing Firms″. International Journal Of Economics, Finance And Management Sciences1(2), 68. http://dx.doi.org/10.11648/j.ijefm.20130102.12

Forsberg, A., & Saukkoriipi, L. (2007). Measurement of waste and productivity in relation to lean thinking. In Proceedings IGLC-15. Michigan.

Gupta, S., & Jain, S. (2013). A literature review of lean manufacturing. International Journal Of Management Science And Engineering Management8(4), 241-249. http://dx.doi.org/10.1080/17509653.2013.825074

Hicks, B. (2007). Lean information management: Understanding and eliminating waste. International Journal Of Information Management27(4), 233-249. http://dx.doi.org/10.1016/j.ijinfomgt.2006.12.001

Hosseini, S., Nikakhtar, A., Wong, K. and Zavichi, A. (2012). Implementing Lean Construction Theory into Construction Processes' Waste Management. ICSDC 2011.

Ohno, T. (1988). Toyota production system. London: CRC Press, p.9.

Jimmerson, C., Weber, D., & Sobek, D. (2005). Reducing Waste and Errors: Piloting Lean Principles at Intermountain Healthcare. The Joint Commission Journal On Quality And Patient Safety31(5), 249-257. http://dx.doi.org/10.1016/s1553-7250(05)31032-4

Jones, D., & Womack, J. (2014). Lean thinking. United States: Free Press.

Lacerda, A., Xambre, A., & Alvelos, H. (2015). Applying Value Stream Mapping to eliminate waste: a case study of an original equipment manufacturer for the automotive industry. International Journal Of Production Research54(6), 1708-1720. http://dx.doi.org/10.1080/00207543.2015.1055349

Mezgebe, T., Asgedom, H., & Desta, A. (2013). Economic Analysis of Lean Wastes: Case Studies of Textile and Garment Industries in Ethiopia. International Journal Of Academic Research In Business And Social Sciences3(8). http://dx.doi.org/10.6007/ijarbss/v3-i8/123

Modi, D., & Thakkar, H. (2014). Lean thinking: Reduction of waste, lead time, cost through lean manufacturing tools and technique. International Journal Of Emerging Technology And Advanced Engineering4(3), 339-344.

Senaratne, S., & Wijesiri, D. (2008). Lean construction as a strategic option : Testing its suitability and acceptability in Sri Lanka. Construction Management and Economics2008, 34-48.

Vamsi Krishna Jasti, N., & Kodali, R. (2014). A literature review of empirical research methodology in lean manufacturing. International Journal Of Operations & Production Management34(8), 1080-1122. http://dx.doi.org/10.1108/ijopm-04-2012-0169

MBA

Select your study program:

MBA Program

 

DBA

Choose your field of specialization:

 

MSc

Choose your field of specialization:

 

Ph.D.

Choose your field of specialization:

 

close
LIGS logo white color

Last chance to enroll Ph.D. & DBA!
Get 25% off the Tuition by enrolling now. Only few spots left!

Due to demand, we are stopping intake of new Ph.D. & DBA students.
Apply now and study with a decreased tuition!

Interactive online Ph.D.
 

More information

 

Interactive online DBA
 

More information