Product development sequential

Product development models are the driving force for delivering the product to market on time and at the right cost. In general, the models in the literature can be divided into just two types sequential and concurrent. Each has its own characteristics, but there are several requirements that a new product development model should fulfil (Sum, 1992) ... 

Figure 5.6 Sequential versus concurrent model for product development (Maylor, 1996)...

The automotive sector s quality assurance standard QS 9000 (1998) suggests a concurrent high level model, as opposed to the sequential model from BS 7000 (1997). This is shown in Figure 5.7. The automotive industry in particular has embraced the use of concurrent engineering models for product development, and this is reflected in the standards which facilitate their quality assurance programmes. A concurrent industrial model from the automotive sector will be discussed later. 

Anaerobic bioreactors have been used since the 1880s to treat wastewaters with large amounts of suspended solids. However, anaerobic reactors are sensitive to toxic pollutants and vulnerable to process upsets, and have been used mainly for municipal sludge digestion. For methane production the sequential metabolism of the anaerobic consortia must be balanced, and the methanogens in particular are vulnerable to process upsets. Recently, anaerobic-aerobic processes (Figure 1.1) have been developed for the mineralization of xenobiotics. These processes take advantage of an anaerobic reactor for the initial reductive dechlorination of polychlorinated compounds or the reduction of nitro substituents to amino substituents. If the reduced compounds are more readily mineralized in an aerobic reactor, an anaerobic-aerobic process is feasible. 

If the cost of delay in lead-time is low it is usually because the product has a long lifetime once in the market the customer once committed to the product will stay with it for a long time. If this is coupled with a high product risk, i.e. the product is expensive and needs a guaranteed customer, then a particular situation arises where it is best developed sequentially, as part of a series. An example outside the chemical field would be a range of aircraft such as the Boeing 747, 757, 767 series. 

Furthermore, the expression mechatronic approach is common in product development. That is, that the traditional sequential design procedure (mechanics —> electronics control/ communication), which results in partly optimized products and time- and cost-intensive iterations, is overcome and replaced by an interdisciplinary cooperation of the development teams in the sense of concurrent engineering (van Brussel 1996). Thus, optimal products can be developed at reduced costs. 

Furthermore, SE specifies that the inputs for the creation of physical models are to be provided by the logical model that represents the systems view (Fig. 9.7). This enables therefore the parallel creation of domain specific models instead of a sequential development of the physical models, that would be driven by the mechanical design. Since concurrent engineering addresses the parallelization of diverse phases and processes of product development, it can be considered as a complementary for systems engineering. 

System safety is effectively a risk management process that deals on hazards, potential mishaps, and risk. System safety is involved in many different aspects of system/product development however, it is structured around the six core elements that form the system safety process. These six elements are the building blocks that shape a foundation for the SSP. Rgure 2.87 shows the core system safety elements and their interrelatedness. This viewpoint shows the core process as a sequence of tasks however, in reality, they are quasi-sequential steps as the process has many iterations and interrelationships. 

Xhe current technological DIRECnONS in polymer-related industries in the 1990s have been driven and shaped the operative business and societal forces. These forces strongty affect and influence the product development process, which is no longer a sequential process from research and development (R D) to product introduction into the marketplace. This process of necessity has become highty nonlinear, nonsequential, and iterative in order to shorten the time from product elop-ment to market introduction. 

It is the classical (albeit too simplicistic) sequential view of the innovation process, where e.g. product development follows so-called applied research using itself results from basic research. Fortunately, it is more and more accepted that actual iimovation processes are more complicated in the sense that e.g. feedback from the "later" stages of the process to the "early" stages of the process are rather important, e.g. the course of activities often qualified as "basic research" may well be implicitly or explicitly influenced by possible applications. 

Numerical results show that the solution calculated by the integrated approach offers improved performance over the sequential approach. Certainly, the optimal expected CV from the integrated approach (lA) is considerably higher than the one computed by utilizing sequential approach (SA). The lA renders an expected CV of 14.3 X 10 m.u. while a CV of 2.79 x 10 m.u. is obtained by applying the SA (see Table 3.1). The two approaches also yield different project selection decisions as shown in Fig. 3.6. The SA launches the product development process for P4 in first period, P6 in second period, and P5 in fifth period, while the lA launching policy is P6 in first period and then waits until the fourth period to launch P5. It is important to point out that the sequential approach selects the projects based on the NPV. 

Control charts were originally developed in the 1920s as a quality assurance tool for the control of manufactured products.Two types of control charts are commonly used in quality assurance a property control chart in which results for single measurements, or the means for several replicate measurements, are plotted sequentially and a precision control chart in which ranges or standard deviations are plotted sequentially. In either case, the control chart consists of a line representing the mean value for the measured property or the precision, and two or more boundary lines whose positions are determined by the precision of the measurement process. The position of the data points about the boundary lines determines whether the system is in statistical control. 

Two newer areas of implantation have been receiving attention and development. Focused ion beams have been iavestigated to adow very fine control of implantation dimensions. The beams are focused to spot sizes down to 10 nm, and are used to create single lines of ion-implanted patterns without needing to create or use a mask. Although this method has many attractive features, it is hampered by the fact that the patterning is sequential rather than simultaneous, and only one wafer rather than many can be processed at any one time. This limits the production appHcations of the technique. 

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