Question 3 of 7: Product Design Approaches, Criteria and Simulation

Question 3: Product Design Approaches, Criteria and Simulation (20 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

(i) Sequential versus Simultaneous Integrated Design

Sequential design—the traditional "over-the-wall" approach—develops a product in a strict linear sequence of separate stages: marketing defines the need, design engineering creates the design and passes it to manufacturing, which then works out how to make it, after which quality and service deal with the consequences. Each function completes its work and hands off to the next, largely in isolation. Its weaknesses are serious: manufacturing and quality problems are discovered late, when changes are expensive; the hand-offs are slow, lengthening time to market; and the lack of early collaboration produces designs that are hard or costly to make. Simultaneous (concurrent or integrated) design, by contrast, brings all relevant functions—design, manufacturing, quality, purchasing, marketing, and often suppliers and customers—together from the outset to work in parallel on the product and its production process at the same time. Using multidisciplinary teams, it considers manufacturability, quality, cost, and serviceability while the design is still fluid and cheap to change. The benefits are shorter development time (parallel rather than serial work), lower cost (problems caught early), higher quality, and smoother production launch. Concurrent engineering is the modern standard precisely because it replaces costly late rework with early, collaborative problem-solving.

(ii) Design Criteria in Product Development

Developing a product requires balancing a set of design criteria so that the result satisfies customers, the business, and society. Functionality and performance—the product must do what it is intended to do, reliably and to specification—come first. Quality and reliability ensure it performs consistently over its expected life with acceptable failure rates. Cost (manufacturability and economy) requires that it can be produced economically at the target price, which links directly to design for manufacturability. Safety is paramount—the product must not endanger users, and must meet codes and standards. Ergonomics and usability make it convenient and comfortable to use, while aesthetics address appearance and appeal. Maintainability and serviceability allow economical repair and support, and durability ensures adequate service life. Increasingly important are environmental and sustainability criteria—efficient use of materials and energy, recyclability, and low environmental impact—and regulatory and standards compliance. Finally, time-to-market and compatibility/standardization with existing systems weigh in. Good design consciously trades off these often-competing criteria rather than optimizing one at the expense of the rest.

(iii) Use of Simulation Models in Production

Simulation modelling builds a computer model of a production process or system and runs it to imitate the system's behaviour over time, allowing engineers to study, track, and improve the process without disturbing the real operation. Its uses in tracking production and identifying problems are substantial. It lets engineers identify bottlenecks—the stations or resources that constrain throughput—by observing where work-in-process accumulates and queues form. It supports capacity and resource analysis, revealing utilization of machines and labour and the effect of adding or removing resources. It enables "what-if" experimentation—testing changes to layout, scheduling, batch sizes, or staffing safely and cheaply in the model before committing to them in reality. It captures variability and randomness (machine breakdowns, variable processing and arrival times) that static calculations miss, giving realistic estimates of throughput, cycle time, and queue lengths. It helps diagnose problems such as excessive waiting, blocking, or starvation, and to validate proposed solutions. Common tools model discrete-event systems and are widely used in manufacturing, logistics, and service operations. By experimenting on the model rather than the plant, simulation reduces the cost and risk of process design and improvement.

Practical Application

A firm developing a new appliance would use concurrent (simultaneous) design, seating manufacturing and quality engineers with the design team so that the housing is designed for easy assembly from the start, balancing performance, cost, safety, and recyclability criteria. Before installing the assembly line, it would build a discrete-event simulation of the proposed line, revealing that a testing station is the bottleneck; "what-if" runs would show that a second tester raises throughput enough to meet demand—an insight gained cheaply in the model rather than after costly installation.