Metallurgic Technologies: Improving productivity

In January 2014, Clarence Tan, CEO of Metallurgic Technologies (Metatech), an equipment manufacturer for upstream oil and gas companies, faced a challenging situation. Tan had won a contract to manufacture internal valve kits for a major customer assembling wellhead components. These valve kits acte...

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Bibliographic Details
Main Authors: KOH, Niak Wu, CHAN, Chi Wei
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
Subjects:
Online Access:https://ink.library.smu.edu.sg/cases_coll_all/194
https://cmp.smu.edu.sg/case/2511
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Institution: Singapore Management University
Language: English
Description
Summary:In January 2014, Clarence Tan, CEO of Metallurgic Technologies (Metatech), an equipment manufacturer for upstream oil and gas companies, faced a challenging situation. Tan had won a contract to manufacture internal valve kits for a major customer assembling wellhead components. These valve kits acted as taps for the wellhead, and were important in controlling the flow of oil. However, Tan was worried about breaking even on his latest contract. Since he had entered the bid, raw material costs had gone up. Manpower costs had also been on an upward trend for many years. Metatech’s business environment was high mix and low volume, which meant that contracts were typically for small quantities. In order to survive the industry’s intense competition, the company had to take on multiple contracts for different parts simultaneously. Metatech’s production processes were highly automated and each machine could be adapted for various uses. Tan had 12 months to fulfil the order. The manufacture of valve kits involved four steps comprising cutting, drilling, machining and degreasing. He wanted to review the current status of the machine shop process and further improve productivity. Through this case, the participants will have an opportunity to learn about the competitive nature of the oil and gas services industry. This case would help participants identity process bottlenecks and determine efficient batch sizes to minimize costs.