What type of operations focus on products in the early stage of the life cycle?

3.1 Introduction

Today's product life cycle of many products is best described by obsolescence before depreciation. Therefore, for companies to survive and prosper in today's global market, they must sell more products, create new product ideas, and convert their intellectual properties to true market opportunities. Dwelling on the success of a current product will be a short-lived prosperity, and companies must always prepare for the next leading product. Unfortunately, product development can indeed be very risky and substantially costly, particularly when it is not done properly or when it involves major changes in existing operations or requires new technologies. To make matters additionally complex, a product development process, no matter how seemingly organized, may not always result in a product that will draw consumer's interest from the get-go. In the US market, estimates of the failure rate of industrial new products, determined by the significance in return, have increased from about 35% in the late 1980s to more than 50% in the 2000s [1,2]. Estimates of new product failure rates will vary widely by company, product category, and industry. However, competition is tougher than ever, and consumer's choices are hardly predictable.

In general, a failure of a new product can be attributed to many factors [1–5], some of which are marketing related and other are design related. Marketing-related factors may include the following: (1) inadequate market analysis leading to misunderstanding of consumer needs and wants; (2) inadequate cost analysis leading to higher cost and overvaluing a product; (3) strong competitor reaction; (4) delayed or rushed product time to market; (5) targeting wrong markets; (6) existence of similar products at lower prices; (7) too much reliance on the success of existing brands in promoting new products; and (8) other factors associated with delivery, tariffs, safety, and trade regulations. Design-related factors may include the following: (1) using old solutions to design new products; (2) less-than-optimal functional performances; (3) problems with patent, license, or copyright issues; (4) more focus on functionality at the expense of style, appearance, and ease to use; (5) performance and quality problems not foreseen at the design stage; (6) safety issues unaccounted for in the design analysis; and (7) poor coordination between product design and product manufacturing.

In today's market, products are sold to consumers of immense diversity of needs and wants. However, consumer's feedback on the performance of products is often limited to a database reflecting complains or rejects of products due to various types of dissatisfaction. In a typical organization, this database only represents less than 5% of product's users, and it should be taken seriously as it may reveal problems that were not foreseen in the product development stage. However, products are often returned and replaced without a question asked, as a result of the classic business wisdom that the “customer is always right.” This makes the reliance on returns and rejects a very limited source of information on the actual product's performance. On the other hand, how often would a consumer receive a phone call or an email asking about how they feel about the performance of a product he/she bought a year ago? If a product stays in the possession of a consumer for a year or longer, it could be because the product is performing so well or due to the lack of alternative options, which is normally a matter of time before a new product is introduced. This aspect of consumer's feedback is often missing in corporate database. It is important that market research utilizes “big data” approaches by gathering more information about current product's performance and consumer's desire of areas of improvement. In today's information era, “dynamic consumer feedback” should be a part of any organization marketing database. This type of feedback is timely reflective of product's performance and alone can result in stimulating creativity to produce new products or enhance the performance of an existing product.

Traditionally, product development has been known as primarily an engineering job. This was a result of the common perception that product development is merely a process of improving existing products or converting new ideas into innovative products through appropriate design conceptualization and design analysis, which are typically engineering tasks. However, in today's competitive market, the concept of product development has been expanded to accommodate and integrate critical product-related aspects such as consumer's perception, differences between needs and wants, product's attractiveness, value appreciation, market niches, and anticipated performance over a product's life cycle. These aspects are extremely complementary to the design process, but classic engineering education often ignores these aspects as a result of only focusing on product functionality. Therefore, a job description of a product developer today is no longer restricted to engineering background, and it may indeed cover a wider range of disciplines including nonengineering qualifications.

In this chapter, basic concepts and various elements of product development will be discussed by providing a simplified view of the product development system to familiarize the reader with the basic tasks constituting most product development programs. Key elements of product development will include the following: (1) generating product idea, (2) determining and defining anticipated product performance characteristics and related attributes and requirements, (3) the information-gathering process, (4) evaluating the merits of the new idea to justify proceeding forward, (5) design conceptualization and design analysis, (6) mass manufacturing, and (7) marketing.

2.1 Complex engineering product life cycle

The concept of product life cycle comes from the traditional understanding of changes in the sales of a product at different periods, starting from a product’s introductory phase. For complex engineering products, a more formalised and visible management structure is required to manage the product life cycle. The challenge lies in consolidating and exploiting the knowledge in the virtual enterprise in order to fulfil the enterprise mission. The life cycle of a virtual enterprise begins when one or more of the partner companies sees business opportunities and invites the other companies in the business network to join the virtual enterprise. To support the operation of a virtual enterprise, the partner companies are not only required to provide resources and equipment for their part of the business but are also required to bring along knowledge and technologies that are appropriate to the virtual enterprise. Such knowledge and technologies are often classified as intangible assets because they are usually brought to the virtual enterprise by teams of people assigned to it, and because they will vary when different groups of people are involved. The highly unpredictable and invisible nature of these intangible assets makes it difficult for the virtual enterprise to create, control, maintain and share them among partners.

Complex engineering products are data-rich, knowledge-intensive outcomes. At first, the knowledge part is the intangible asset of the supplier. However, to effectively manage and operate the complex engineering product after commission, the owner or contractor doing the support work must acquire the same or an even better level of knowledge. To do this, it is necessary to understand the nature and characteristics of an intangible asset within the life cycle of the product with which it is associated.

The design of systems can vary greatly among vendors and concepts. In many cases, several consortia are involved and each brings its own expertise and expectations. The challenge to the system acquisition team is to establish suitable baselines for comparing different proposals. The acquisition process, which is already lengthy and complicated, is further complicated by the expectation that a complex engineering system must remain in service for years. This expectation is becoming more common.

From the owner’s point of view, asset capability should increase over time to meet changing demands. To achieve this goal, typical support and services after acquisition of the asset should be included; two examples would be significant mid-life upgrades and continuous whole-system integrated logistics support. The philosophy of whole-of-life engineering development and support is to integrate design information with specific knowledge about implementation, manufacturing, servicing and decommissioning of the product. In addition, substantial planning is required to enable flexible delivery of service and logistical support to the asset from anywhere in the world.

16.6 Product life cycle

The product life cycle is the period of time over which an item is developed, brought to market, and eventually removed from the market due to reduction of demand for that item.

From the 1950s and 1960s and for more than 30 years, when it was a seller’s market in India, Ambassador or Fiat cars were running without any change in the shape or other features. But today with so many varieties of cars available with added features, car manufacturers must keep improving features to attract customers. Similar is the case with the desktop computers compared with today’s laptops. Manufacturers must continue adding new features every 3 to 5 months to sustain the market. This 3-month period is called the product life cycle (Table 16.1).

Table 16.1. Forecasting methods for product life cycle.

The four phases of product life cycle are the following:

Introduction phase

When the product is brought into the market. In this stage, there's heavy marketing activity and product promotion and the product is put into limited outlets in a few channels for distribution. Sales take off slowly in this stage. The need is to create awareness, not profits.

Growth phase

The second phase is growth. In this stage, sales take off, and the market knows of the product; other companies are attracted, profits begin to come in, and market shares stabilize.

Maturity phase

The third phase is maturity, where sales grow at slowing rates and finally stabilize. In this stage, products get differentiated, price wars and sales promotion become common, and a few weaker players exit.

Decline phase

The fourth phase is decline. Here, sales drop, as consumers may have changed, or the product is no longer relevant or useful. Price wars continue, several products are withdrawn, and cost control becomes the way out for most products in this stage (Fig. 16.2).

Information Assessment

Given the asymmetric information in every step of product life cycles, chances are high that product qualities deviate from stakeholders’ preferences. Various methods aimed at mitigating these deficiencies are introduced. Some methods aim to assess the suppliers’ reliability. There are two approaches. The first approach is tracking record of the suppliers’ outputs, for example, revenues or customer satisfaction. The second one is the suppliers’ inputs, for example, successful ideas or research expenditures. Having a limited track record is usually considered to be poor quality, but the contrary is often observed because newcomers aim to satisfy customers at their best and high inputs do not guarantee good results. The content is also assessed through product tests. Some testing methods address resource uses, for example, energy analyses. Other methods assess impacts, for example, toxicity. Some assessments compare products’ life cycles with one another; others use targeted performance as a basis for comparison. External expertise is often involved in such life cycle assessment. This involvement aims to mitigate biases but the choice of experts and interpretation of expertise cannot avoid biased favorites. Given the risk-avoiding behavior of organizations, it is observed that mediocre qualities are favored. The highly performing but unconventional qualities are usually neglected because they are considered to be uncertain. Evaluations do not resolve much, but do add to administration. Asymmetric information is an unsolvable issue if one strives for the symmetry between suppliers and customers. A radical departure from this objective is advocated by some scholars on entrepreneurship. They argue that the information asymmetry enables entrepreneurial action because suppliers of the novel qualities can accrue competitive advantages, due to imperfect customer knowledge about all product qualities. From this perspective, sustainable technologies are opportunities for suppliers because enable sales of services aiming at cost-effective prevention of the societal costs.

One of the most important considerations in the product life-cycle of an embedded project is to understand and optimize the power consumption of the device. Power consumption is highly visible for hand-held devices which require battery power to be able to guarantee certain minimum usage/idle times between recharging. Other main embedded applications, such as medical equipment, test, measurement, media, and wireless base stations, are very sensitive to power as well – due to the need to manage the heat dissipation of increasingly powerful processors, power supply cost, and energy consumption cost – so the fact is that power consumption cannot be overlooked. The responsibility for setting and keeping power requirements often falls on the shoulders of hardware designers, but the software programmer has the ability to provide a large contribution to power optimization. Often, the impact that the software engineer has on the power consumption of a device is overlooked or underestimated. The goal of this chapter is to discuss how software can be used to optimize power consumption, starting with the basics of what power consumption consists of, how to properly measure power consumption, and then moving on to techniques for minimizing power consumption in software at the algorithmic level, hardware level, and data-flow level. This will include demonstrations of the various techniques and explanations of both how and why certain methods are effective at reducing power so the reader can take and apply this work to their application immediately.

1.3.3 Applications of digital twin

The DT has been applied into various stages of product life cycle. From the perspective of article number, there are more studies focusing on DT in the production stage (e.g., human–machine interaction [59], process planning [30], and energy consumption management [60]), and service stage (e.g., prognostics [3], maintenance [4], and recycling [61]) [44]. It is because, on one side, under the background of smart manufacturing, DT has been highly valued and spread in the manufacturing field as a promising technology for cyber-physical fusion, which attracts lots of attentions; and on the other side, since the DT application starts from prognostics and health management [40], it has been developing for a longer period in the service stage. By comparison, there is not much concern for applying the DT in the product creation stage (i.e., the design stage). However, as stated by Dassault, the DT has huge potential in design [62]. What is more, if a product DT model could be established from the design phase, then more related design data, marketing data, and user experience data can be integrated, which will result in better services for the production and after-production stages [1].

Some current DT applications in the design stage have been investigated in the authors’ previous works [1,39,44]. For example, Zhuang et al. [63] explored the connotation, architecture, and trends of DT in terms of product and suggested some relevant theories and tools to implement the DT-based product design. Canedo [64] believed that product design could be notably improved by adding data from DT. Yu et al. [65] proposed a new DT model to manage the 3D product configuration, which could reinforce the collaboration between design and production. Tao et al. [1] explored a DT-driven product design framework to facilitate the design phases such as task clarification, conceptual design, and virtual verification. Schleich et al. [66] put forward a DT model to manage geometrical variations, in order to evaluate part deviations of a product at the early stage. Zhang et al. [67] studied a DT-based approach to design production lines, taking a glass production line as an example. Ferguson et al. [68] yielded a DT-based damage prediction method for water pumps to address certain design challenges. Mavris et al. [69] explored a design method based on the DT and digital thread for an aircraft.

It is expected that by using the DT, experimental, actual measurement and calculation can be integrated, and the real-test environment parameters can also be integrated. For designers the DT serves to provide affordance information, identify and diagnose various complexities associated with a product, and guide designers to formulate rational functional requirements. For customers the DT serves to meet customer needs and to deepen designers’ understandings. In addition, the product use in actual conditions could be accurately simulated.

5.2.2.1 Data and Data Quality

13.2.1.3 Data and Data Quality

3.1 Introduction

The transition to the circular economy (CE) and sustainable development is posing new challenges to the construction and demolition waste (C&DW) sector for the purpose of guiding it to balance better the goals of socioeconomic development with the ones of better environmental protection involving a reduction of resource materials’ exploitation and waste production (Rau and Oberhuber, 2019; Adams et al., 2017).

The strategical framework of the CE focuses on some building blocks depicted in Fig. 3.1 which aims to manage better the use of finite stocks of natural resources and optimize resource productivity by retaining as long as possible the value of products, components, and materials in use in both technical and biological cycles (Ellen MacArthur Foundation, 2017). The final goal is to improve the effectiveness of the economic system by revealing and designing out negative externalities (Ellen MacArthur Foundation, 2017) related to the use of natural resources, emissions release, and waste generation.

The implementation of the CE entails the adoption of more sustainable practices in the whole life cycle of products or systems (e.g., C&D projects related to buildings or infrastructures) (Ghisellini et al., 2018, b), the boundaries of analysis of which are based on the concept of “cradle to cradle” (Braungart et al., 2008).a This approach focuses on resource materials (in particular technical materials) that flow continuously in a system as products and their components are designed and optimized for a cycle of disassembly and reuse (Moreno et al., 2016; Ellen MacArthur Foundation, 2012).

From a life-cycle thinking perspective it implies to consider the environmental and socioeconomic impacts (Hossain and Ng, 2019; Hossain et al., 2017; Di Maria et al., 2018) related to all the processes from the extraction of resources, manufacturing, maintenance and repair, reuse and recycling of waste materials from a product and using these materials again and again for producing new products (Dieterle et al., 2018) (Fig. 3.2).

For example, in the construction sector the concept of buildings as “material banks” has been developing (European Union, 2019), highlighting the importance that each material should be designed for recoverability as well as its identity is stored in a database (Rau and Oberhuber, 2019). In that the constructor or the owner should establish an intimate relationship with the building, its component materials, and be responsible for their destiny. This hopefully should act as an antidote to move beyond our “throwaway society” (Castellani et al., 2015; Stahel, 2013).

Recycling of C&DW is one of the available and relevant practices within the circular patterns and business models and in the wider framework of sustainable construction measures that favor prevention over mitigation of the environmental impacts of the C&D industry. Recycling as a mitigation measure bears positive and negative impacts (Silva et al., 2017) and the inclusion in CE framework is important to maximize the quality of the recycling process and preserve the integrity of material recycling (Den Hollander et al., 2017). In that the CE requires favoring a particular form of recycling, the so-called “upcycling” versus the actual most practiced “downcycling” (Dieterle et al., 2018).

In this initial stage of transition toward the CE that is characterized by uncertainty of the outcomes (Lahti et al., 2018), the assessment of the sustainability of circular patterns and business models for reuse/recycling of C&DW provides a useful framework for supporting decision-making at both private and political levels.

This chapter deals with the economic impacts of circular patterns and business models for reuse and recycling of C&DW and presents an overview of the most recent results coming from the available economic and financial studies that evaluate the economic performances of recycled products from C&DW. The assessment will be supported by data on the reuse/recycling of C&DW at the global level, on the products that can be derived from C&DW and the main barriers that such products as well as the general implementation of circular patterns for the management of C&DW are experiencing.

The study aims to complement the available international literature, which mainly addresses the environmental performances of secondary products from C&DW by means of the life-cycle assessment approach (Vilches et al., 2017; Vieira et al., 2016; Bowea and Powell, 2016; Lu and Yuan, 2011), with the final purpose to contribute to promote further research on these topics.

Abstract

Life Cycle Assessment or LCA is a technique to evaluate environmental impacts through the entire life cycle of products and/or processes, which is an important key to identify the environmental hotspot and make more informed decision for process design. In order to perform LCA, LCSoft has been developed with ability to integrate with other process design tools such as process simulation software, economic analysis tool, and sustainable process design tool. In addition, several optional interpretation features are available, such as, sensitivity analysis, alternative comparison, and eco-efficiency evaluation. More specifically in this paper, LCSoft has been improved in terms of performance and application range. The development framework consists of four tasks. The first task deals with a new pathway for LCIA calculation to improve the flexibility of the software. The second task consists of extension and management options of Life Cycle Inventory database. The third task deals with development & introduction of new LCSoft features - parameter sensitivity analysis, normalization, and data quality indicator. The final task is validation of the integrated software. In this paper, assessment results for bioethanol production from cassava rhizome are compared with LCA software, SimaPro. The results indicate that the new features of LCSoft provide reliable calculations very efficiently, and are especially useful for chemical and biochemical sustainable process design studies.