Praaktoodetest põhjustatud kulude vähendamine

Lõputöös analüüsiti praagi tekkimise põhjuseid, ka võimalusi ja tekkimiskohti läbi lean 6δ timmitud tootmise printsiibi, kasutades DMAIC samme. Analüüsi eesmärgiks oli määratleda ja edasi vähendada 7 raiskamisest tulevaid kulutusi. Analüüsist selgus, et suurel ettevõttel nagu seda on Ericsson, on küll tugevad kvaliteedi haldamise meetodid, siiski leidub probleeme, mida võime leida igas tootmisettevõttes, mis vajavad kõrvaldamist kvaliteedipõhise kasumi tõstmiseks. Lõputöös käsitleti trükkplaatidega valmistamisega seonduvaid praagitekkeid valmistamise erinevais etappides, analüüsiti tekkepõhjuseid ning esitati konkreetseid parendusettepanekuid põhjuste kõrvaldamiseks. Ettepanekud on olulisel määral rakendatud. Trükkplaatide valmistamise praagiprobleemide Lean 6δ analüüsi ja 5S võtete rakendamise tulemuseks oli märkimisväärne, kuni 57%line vähenemine paranduses olevate plaatide kogusest. Vigade tekkimise võimaluste vähenemise tõttu on vähenenud ka trükkplaadi kooste praagu hulk on vähenenud rohkem kui 44%. Trükkplaatide funktsionaalsete vigade tekkepõhjuste seletamise järgselt kasvas töötajate individuaalsete töösoorituste tase ja tootekvaliteet. Tööjuhenditesse viidi sisse sellekohased muutused tagamaks tehtud parenduste järjepidevus. Samuti aitas praagi kulude vähendamisele kaasa konkreetsete tootmisosade andmebaaside loomine, mis andis inseneridele parema ülevaate toodetega toimuvast. Andmebaasid paranduses olevate toodete kohta näitasid ära, kui kaua ja mis põhjusel on toode parandusse toodud ja kui kaua võtab veaotsijal ühe või teise veakoodi parandamine aega, läbi selle sai juhtida veaotsijate koormust ja tagati paranduse kvaliteet. Tootmise pidev kontroll aitab kiiremini reageerida vastavatel töötajatel probleemide lahendamiseks, et probleem ei eskaleeruks.

Title of this final thesis is „Scrap cost reduction“. The objective of this thesis was to analyse and reduce scrap quantities and costs, also production associated costs for scrap at the Ericsson Supply Site Tallinn. To reach the objective, the following quality methods were used: Lean 6δ, DMAIC, 7 + 1 wastes, 5S. The analysis consists of production data analysis, according to lean 6δ DMAIC methods. According to what production step the problem occurs in, the product that was connected with this issue, and what causes the issues and the product components that had the biggest influence on scrap costs. Data that is used comes from databases that the supply site uses in production to measure results. In todays production there are lots of different quality systems and methods to control and develop production and the products quality. Analysis revealed that most problems that occur in Ericsson Supply Site Tallinn also occur in other supply sites. A lot of the production goes through manual operations, and this affects the product quality. That`s why the company must have a will to motivate people using various incentives. Trouble shooters skills and testing equipment are the most important factors in finding issues on printed circuit boards. It also requires a lot of development in test technology. The more accurate the equipment is, the better the trouble shooter’s capability to find the problems will be. One important part of the fault analyses is the follow-up of analyses this helps to understand the causes of the issues, and through that helps to improve the production. Finding out what caused the mistake may not prevent the product from being scrapped, but helps to avoid problems in the future. By using Lean 6δ analysis and applying 5S solutions the company has reduced repair buffers volumes approximately 57%. It also helps to reduce risks that may occur in repair buffer and it may have an impact on the scrapped printed boards cost and volumes. Explaining the issues in the functional faults area the company have increased the knowledge of trouble shooters whose work is now have a higher quality and also the products quality has risen. All together the company has saved 44% total of the printed circuit boards scrap costs. Also making the repair databases more accurate helped to reduce scrap costs, because it simplifies the control of the system and it is the fastest way to see when problems occur. The repair buffer database now shows how long the product has been in repair buffer and why. It also shows how long it takes to repair a particular product. The database helps to plan the trouble shooters work time and improve repair quality. Continuous control of data helps to react quickly when problems occur and the company can implement continues improvements so that problems will not escalate. Continues improvement is always ongoing.