This research work proposes a new methodology for implementing Value Stream Mapping, in processes that feature a High-Mix, Low-Volume product base. The opportunity for adapting the methodology singularly for these types of environments was identified because implementing Value Stream Mapping as proposed in Learning to See features several drawbacks when implemented in High-Mix, Low-Volume. Although Value Stream Mapping has been proven to enhance many types of processes, its advantages are shrunk if they are implemented in High-Mix, Low-Volume processes. High-Mix, Low-Volume processes are types of processes in which a high variety of finished goods are produced in relatively low amounts. The high variety of finished goods causes several complications for the implementation of flow. The difficulties that prevent the flow are the following: The variance in the products: With hundreds, or sometimes thousands of possible finished goods, the number of products causes a non-repetitive process. The variance in the routings: All of the products that are produced can have completely different process routings, or order of stations it has to visit. This makes the application of production lines quite difficult. The variance in the cycle times for each process. Each of the different products can have completely different capacity requirements at a specific machine, which limits the predictability of the process. This purpose of the thesis is to gather the best practices for controlling and improving High-Mix, Low-Volume processes and merge them with some innovative ideas to create an inclusive Value Stream Mapping methodology which is better fitted with the types of complications in High-Mix, Low-Volume environments. In parallel, the methodology is tested with the company: Boston Scientific, in their Ureteral Stents manufacturing process. The real-life experimentation will allow for the fine-tuning of the methodology, in order to truly create impact in the process.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-102839 |
| Date | January 2012 |
| Creators | Araya, Juan Manuel |
| Publisher | KTH, Industriell ekonomi och organisation (Avd.) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Examensarbete INDEK ; 2012:120 |
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