Production companies face the challenge of choosing a suitable process optimization method
from a variety of methods, even though their effect on operational processes is uncertain.
This study shows, using a statistical hypothesis test, the impact of the methods Kanban
and Standard Worksheet on an autonomous team in comparison to a team that applies
these methods. For this purpose, 44 companies – of different size and operating in various
industries – across Germany completed a business game and generated data regarding the
KPIs adherence to delivery date, number of reworks and inventory costs. Based on these
data, the team’s performance could be ascertained and compared with each other.
Recently, aluminum matrix syntactic foams (AMSFs) have become notably attractive for many different industrial areas like automotive, aerospace, construction and defense. Owing to their low density, good compression response and perfect energy absorption capacity, these advanced composite materials are also considered as strong alternatives to traditional particle reinforced composites and metal foams. This paper presents a promising probability of AMSF fabrication by means of industrial cold chamber die casting method. In this investigation, contrary to other literature studies restricted in laboratory scale, fully equipped custom-build cold chamber die casting machine was used first time and all fabrication steps were designed just as carried out in the real industrial high pressure casting applications. Main casting parameters (casting temperature, injection pressure, piston speed, filler pre-temperature and piston waiting time) were optimized in order to obtain flawless AMSF samples. The density alterations of the syntactic foams were analyzed depending upon increasing process values of injection pressure, piston speed and piston waiting time. In addition, macroscopic and microscopic investigations were performed to comprehend physical properties of fabricated foams. All these efforts showed almost perfect infiltration between filler particles at the optimized injection parameters.