A new lightweight design method integrating shape optimization with life cycle assessment for extrusion dies

Accepted Manuscript A New Lightweight Design Method Integrating Shape Optimization with Life Cycle Assessment for Extrusion Dies

Yan He, Tao Huang, Yan Wang, Yi Nie, YuFeng Li, Yulin Wang PII:

S0959-6526(17)30412-2

DOI:

10.1016/j.jclepro.2017.02.186

Reference:

JCLP 9112

To appear in:

Journal of Cleaner Production

Received Date:

02 March 2016

Revised Date:

02 February 2017

Accepted Date:

25 February 2017

Please cite this article as: Yan He, Tao Huang, Yan Wang, Yi Nie, YuFeng Li, Yulin Wang, A New Lightweight Design Method Integrating Shape Optimization with Life Cycle Assessment for Extrusion Dies, Journal of Cleaner Production (2017), doi: 10.1016/j.jclepro.2017.02.186

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

ACCEPTED MANUSCRIPT 1

A New Lightweight Design Method Integrating Shape Optimization with Life

2

Cycle Assessment for Extrusion Dies

3

Yan Hea, Tao Huanga, Yan Wangb, Yi Niec, YuFeng Lia, Yulin Wang d, *

4

a State

Key Laboratory of Mechanical Transmission, Chongqing University, China

5

b Department

6

c Faculty

7

d School

of Computing, Mathematics and Engineering, University of Brighton, UK of Science and Engineering, University of Nottingham Ningbo, China

of Mechanical Engineering, Nanjing University of Science and Technology, China

8 9

Abstract

10

Extrusion dies, in which melted raw materials are forced continuously into a profile to produce various

11

plastic products, are often empirically designed leading to overweight and waste in materials, energy

12

and emissions. Lightweight design method has been applied to reduce weight and increase material

13

efficiency of extrusion dies at design stage. However, the research work was often focused on weight

14

reduction with function requirements as the design constricts. Environmental impacts (EIs) over the

15

entire life cycle of dies are not considered, as a result, it may result in environmental burdens being

16

shifted from design stage to other stages of life cycle of products. Aiming at it, a new lightweight

17

design method is proposed to integrate life cycle assessment (LCA) with shape optimization. The

18

optimization mathematic models for the proposed method are developed, in which the EIs of extrusion

19

dies are modeled as a function of shape variables and processing parameters. An example of extrusion

20

dies for plastic pipe was presented to illustrate the effectiveness of the proposed method. The results

21

showed that 13% weight reduction whist achieving reduction in EIs over the life cycle of dies in

22

comparison with 18% weight reduction yet 29% increase in EIs at manufacturing stage and resultant

23

increase in EIs over the life cycle using conventional lightweight design method in which EIs are not

24

taken into account. It indicated that the proposed lightweight method could have great potentials to

25

reduce weight and prevent environmental burdens shift problem.

26

Key words: Lightweight design; shape optimization; environmental impact; LCA

27 28

1 Introduction

29

Extrusion dies in which melted raw material is forced continuously into a profile are widely used for

30

production of various plastic products. Traditionally, extrusion dies are often over engineered due to

31

lack of advanced numerical simulations, which has directly led to overweight of dies and its associated

32

waste in materials and excessive energy for material extraction, operation and recycling. Some studies

33

on the numerical simulation have been carried out to improve products quality, extrusion performance 1

ACCEPTED MANUSCRIPT 1

(Yilmaz et al., 2014; Chen et al., 2011; Pauli et al., 2013) and design efficiency (Zhang et al., 2015) by

2

optimizing structural and shape parameters of extrusion dies. But few researches have paid attention to

3

lightweight design and environmental performance improvement of extrusion dies.

4

With growing concerns over industrial pollution, increasingly stringent environmental regulations have

5

been implemented in many countries (Zhang, et al., 2016; Yilmaz, et al., 2015). It is imperative for

6

industry to research for solutions not only to increase material efficiency but also enhance

7

environmental performance of products (Pouilikidou et al., 2014). Lightweight design has been widely

8

used to reduce weight and increase resource efficiency of products (Polavarapu et al., 2009; Shea and

9

Smith, 2006; Zhang et al., 2007; Joost, 2012). A lightweight design method based on topology and

10

free-size optimization was proposed by Polavarapu et al. (2009), in which stress and deflection were

11

considered as design constrains and an overall 13% weight reduction was reported. Shea and Smith

12

(2006) suggested a structural topology and shape annealing optimization method to reduce structural

13

mass of transmission tower and the results showed that a mass reduction of 16% was achieved under

14

the constrains of stress, load and compression ratio constrains. Joost (2012) realized a weight reduction

15

of 10% by applying lightweight material in the vehicles in which mechanical requirements were

16

represented by strength and stiffness.

17

Lightweight design is regarded as an important eco-design method as it is widely believed that weight

18

reduction could reduce environmental impacts. Traditionally, lightweight design is conducted by using

19

functions and its associated mechanical performance requirements of products as objectives for

20

optimization and EIs are generally not considered (Strano et al., 2013). To address this issue,

21

Ermolaeva et al. (2002, 2004) proposed a lightweight optimization method based on lightweight

22

materials and structure optimization in which environmental performances were used as one of the

23

decision-making criteria to determine the minimized mass. Holloway (1998) also proposed a material

24

selection method to minimum weight of products and calculating both air and water pollution indices.

25

By producing material selection charts, along the lines of Ashby’s method, which deal with air or water

26

pollution, mechanical design for optimal environmental impact may be structured and accelerated.

27

However, environmental performance of a product is not only affected by material reduction, but also

28

resource consumption and relevant emissions at other life stages such as manufacturing, use and end of

29

life (EOL) stages. The conventional lightweight design methods based on function requirements only

30

does not guaranty environmental gains in the entire life cycle of a product. It may increase EIs at the

31

other stage of the product life cycle. For example, structural optimization in lightweight design method

32

may increase material removal volumes, leading to increase in EIs at manufacturing stage. In other

33

words, lightweight design may reduce EIs at the material extraction stage, but it may result in the 2

ACCEPTED MANUSCRIPT 1

increases at other stages of product life cycle, which could negate initial benefits (Witik et al., 2011).

2

Therefore, lightweight of products at design stage without considering the entire life cycle could

3

potentially lead to environmental burden being shifted from design stage to other life cycle stages.

4

Product life cycle has been considered in light weight design by integrating life cycle tools with

5

lightweight design tools, and the integrated design methods are primarily used to facilitate the effective

6

consideration of environmental aspects during the design process, and eco-innovative product design

7

(Marta et al., 2016). Poulikidou et al. (2014, 2015) reported that lightweight design for materials

8

selection is often focused on performance characteristics, which may lead to sub optimizations of life

9

cycle environmental impact, thus, systematic material selection processes were proposed that integrate

10

weight optimization with environmental life cycle assessment with the design of an automotive

11

components as applications. This proposed lightweight approach is based on material selection which

12

cannot be used for structure-based lightweight design. Andriankaja et al. (2015) proposed a product

13

lifecycle management (PLM)-based lightweight eco-design method. Since a PLM system is to create

14

and manage the product information through its whole life cycle, the PLM-based eco-design method is

15

used to establish an information system linking eco-design approaches with the design process.

16

Therefore, the proposed method is primarily focused on design actions as a generic eco-design tool

17

taking into account product life cycle. Russo and Rizzi (2014a, 2014b) proposed a design method

18

integrating topological and topographic structural optimization as well as environmental performance

19

evaluation to reduce weight and achieve minimum environmental impact of products. Since the

20

topology or topography optimization strategies on components change material distribution and

21

potentially cause thermal stress concentration, they are not suitable to the lightweight of extrusion dies

22

exposed under harsh service conditions such as high-temperature and closed-structure working

23

environment.

24

This paper proposes a new lightweight design method for extrusion dies integrating shape optimization

25

and life cycle assessment based on finite element analysis (FEA) and LCA tools. In this new method,

26

the assessment of EIs is conducted in parallel with the light weight design, so that the environmental

27

burden shift problem caused by the lightweight design could be avoided at early stage. The primary

28

objective is to integrate assessment of EIs with functional requirements as optimization objectives by

29

establishing a mathematical model linking EIs with design parameters and function requirements. The

30

remainder of this study is structured as follows. The next section presents the framework of the

31

proposed lightweight method. Then, the optimization models for the proposed method to assess

32

environmental performance resulted from the geometry lightweight design of extrusion dies is

33

explained in detail in section 3. Section 4 presents a case study for the extrusion dies of plastic pipe to 3

ACCEPTED MANUSCRIPT 1

illustrate the effectiveness of the proposed method, and the discussion of the results and limitation is

2

introduced in Section 5. Finally, Section 6 summarizes the conclusion and the future research.

3 4

2 Framework of the lightweight design method

5

Extrusion dies vary in shape and complexity to meet the demands of products being manufactured

6

(Kostic and Reifschneider, 2006). They are divided into several main categories according to material

7

and shape of head. In this paper, the proposed lightweight optimization method is focused on in-line

8

extrusion dies as the melt exits of die in the shape of annulus. In the optimization process, the key

9

consideration factor is to ensure a proper flow balance of molten extrudates and mechanical

10

performances of extrusion dies. Generally, extrusion dies are composed of many components that vary

11

in types, shape and size such as mandrel, die land, die pin, etc. It is very complicated to take into

12

account assembly relationship among different components in the optimization model, as it would

13

increase optimization cycle time and cost of extrusion dies. Thus, in order to simplify the optimization

14

model and increase design efficiency without sacrificing the overall accuracy, shape optimization is

15

applied to optimize shape parameters of the whole die assembly which are treated as a single

16

component. Meanwhile, in order to meet extrusion performance requirements, the extrusion dies work

17

in a high temperature close to that of the melt extrudate (Miller and Rothstein, 2004). Since shape

18

optimization method does not change material distribution, it can prevent the potential thermal stress

19

concentration caused by material distribution changes, and is suitable for extrusion dies working at a

20

high temperature and closed structure conditions. The process of shape optimization method is realized

21

by optimizing the defined design parameters. The lightweight design method integrating shape

22

optimization and environmental performance evaluation is proposed for preventing environmental

23

burdens shift problems, and the framework of the proposed method is shown in Fig.1.

24

Firstly, design performance indication criteria are identified based on standards or designer’s

25

experiences. FEA method which has been widely used in structural optimization processes (Wang et

26

al., 2003; Fleury and Braibant, 1986; Jin, 2010) is used for the simulation of melt extrudate to analyze

27

the impacts of fluidic behaviors on extrusion dies structure as well as simulation of behaviors of

28

extrusion dies under the fluidic impacts for the prediction of functional performances. In order to

29

evaluate environmental performances of extrusion dies, LCA is used to quantify EIs of extrusion dies

30

from extraction of raw material, manufacturing to final disposal of products. Subsequently, design

31

space for shape optimization of extrusion dies is determined based on results from structural analyses

32

and LCA. Lightweight design method integrating shape optimization and environment performance

33

evaluation is used to achieve the optimized extrusion dies structure. Finally, a comparison of original 4

ACCEPTED MANUSCRIPT 1

design, conventional light weight design and new light weight design considering EIs is made to

2

evaluate the effectiveness of the proposed method.

3

4 5

Fig.1 Framework of the proposed lightweight design method integrating shape optimization and

6

environmental performance evaluation

7 8

As shown in Fig. 1, the proposed method is based on shape optimization method for lightweight

9

design and LCA method for environmental impact assessment in life cycle for extrusion dies. FEA

10

tool is used to analyze the constraints on mechanical performance such as stress, displacement and

11

temperature for the shape optimization, which can make the proposed method valid for the

12

lightweight design of extrusion dies. Furthermore, LCA tool is taken as a scientific, structured and

13

comprehensive tool. It captures the full life cycle of products and allows for direct comparison of

14

products based on the quantitative functional performance of the analyzed alternatives, which is

15

thus suitable to evaluate EIs in entire life cycle for extrusion dies.

16 17

3 Mathematical modeling for shape optimization and environmental impact calculation

18

The primary objective of optimization is to reduce weight whist fulfilling the function performance and

5

ACCEPTED MANUSCRIPT 1

prevent the environmental burdens shift to downstream of the products’ life cycle. Thus, weight

2

reduction and EIs are both regarded as the optimization objectives. Mechanical performance variables

3

such as temperature, stress and displacement are used as the constraint conditions to ensure that the

4

final lightweight structure fulfills the mechanical performance requirements. The EIs of extrusion dies

5

are obtained by LCA analyses based on ISO 14040 and ISO 14044 (2006). The framework of LCA

6

includes (1) goal and scope definition, (2) inventory analysis, (3) impact assessment, and (4)

7

interpretation of results. The scope definition is required to define the product functions, functional

8

unit, reference flow, system boundaries, allocation (Simoes et al., 2013), etc. Eco-Indicator 99

9

methodology, which is a damage oriented approach, is used to evaluate EIs of extrusion dies

10

(Goedkoop, 1999).Combined with eco-indicator definition of LCA, the environment impacts of

11

extrusion dies can be defined as the function equations.

12

The optimization problem based on lightweight design method can be presented as follow:

13

max f(x) = f(x1,x2…,xi,…) (𝑖 = 1,2,…,𝑛);

14

𝑚𝑖𝑛 EILC = f(m, E);

15

St. gj(x) ≤ αg0(x) (j = 1,2…,m);

16

EImaf ≤ EImaf;EIuse ≤ EIuse; EImat ≤ EImat

17

Where f(x) represents the objective function of weight reduction. EILC is the EIs of extrusion dies in

18

full life cycle. gj(x) represents the jth constraint response of mechanical performance. g0(x) represents

19

the mechanical performance boundary condition such as stress and displacement. 𝑥𝑖 denotes the ith

20

design variable of the optimization problem. α is the coefficient used to balance the relationship

21

between mass reduction and structure performance. EImat, EImaf and EIuse are EIs in material,

22

manufacture and use stage, respectively.

23

3.1 Definition of the design variables

24

As shown in equation (1), the design variable xi is used to define the ith available design space of

25

optimization objectives and constrain conditions. The geometrical constrains of design variables are

26

defined as:

0

L

27

0

0

U

(2)

x i ≤ xi ≤ x i L

(1)

U

28

Where x i and x i are the lower and upper bounds of design variables, respectively.

29

3.2 Objectives of structural optimization

30

The weight minimization problem is simplified to reduce components weight of extrusion dies. The

31

weight of each component is related to the type and initial value of design variables. So, the objective

32

function of weight reduction is expressed as following:

33

m

m

02 2 f(x) = ∑1 fm(x1,…,xn,…) = ∑1 (ρmLmπ|xn - xn |)m

6

（3）

ACCEPTED MANUSCRIPT 1

Where f(x) represents weight reduction of extrusion dies; m is the quantity of components, n is the

2

design variable of mth component. ρm is the material density of mth component. Lm is the length

3

coefficient related to volume of mth component. xn is the initial value of design variables.

4 5

0

The stages of life cycle are composed of material stage, manufacture stage, use stage and EOL stage. So, EIs of products in full life cycle are expressed as below:

6

EILC = EIMat + EImaf + EIUse + EIEOL

(4)

7

1) Material and EOL stages

8

Due to the lack of data of material extraction, disposal and recycling, the EIs in material and EOL

9

stages are simplified as being proportional to the weight of raw materials and disposal materials,

10

respectively. So, the EIs in these two stages are expressed:

11

EIMat = βmMat; EIEOL = γmEOL

(5)

12

Where mMat and mEOLrepresent the related weight in material and EOL stages. Weight could be

13

expressed by design variable as equation (3). β and γ is the eco-indicator per unit weight of material in

14

the material and is the eco-indicator per unit weight of material in the EOL stages.

15

2) Manufacturing stage

16

The extrusion dies are composed of many components, each may have different materials and

17

manufacturing processes according to the function and geometry of components. For instance, the

18

semi-finish of extrusion dies may be produced by blanking, which is formed from casting or forging

19

process. Then, further processing may be implemented to achieve the predefined shape of extrusion

20

dies. Generally, rough machining and finish machining are used to ensure final desired cylindrical

21

shape of extrusion dies. Turning and boring may be used to produce the holes on dies. For some

22

especial material and critical components, special manufacturing processes may be needed. Finally,

23

polishing is often used to create a smooth and shiny surface, which can strengthen the material strength

24

owing to the removal of stress concentrations presented in the rough surface. Therefore, change in

25

design variables would affect weight of components and manufacturing processes, which potentially

26

further affects the manufacturing time and energy consumption of components. Therefore, EIs at

27

manufacturing stage are expressed as below: m

28

m n

m

EIMaf = ∑1 EIMaf = ∑1 ∑1EIpron

(6)

m

29

where EIMaf is EIs of mth components. EIpron is EIs of nth machining process including material and

30

energy consumption factors.

31

EIPron = (δmM + εEpron)n

(7)

32

Where δ and ε are eco-indicator per unit weight of material and energy, respectively. mM and EPron

33

represent the weight and energy consumption values of function unit in machining process, 7

ACCEPTED MANUSCRIPT 1 2

respectively. 3) Use stage

3

EIs of extrusion dies at use stage are mainly relevant to the energy consumption of extrusion dies.

4

There are two types of energy consumption models for the use stage including thermodynamic model

5

(Thiriez and Gutowski, 2006; Mattis et al., 1996) and empirical model (Almeida, 2011). The

6

thermodynamic model EThe mainly includes energy consumption of material melting Emelt and

7

extruding materials into extrusion dies Efill. Empirical model EEmp includes energy consumption in

8

temperature controller power and part cooling, which are regarded as a constant in this paper.

9

Therefore, EIs at use stage can be expressed as:

10

(8)

EIuse = ηEuse = η(EThe + EEmp + 𝐸𝑠)

11

(9)

EThe = Emelt + Efill

12

Where η is eco-indicator per unit quantity of energy consumption. 𝐸𝑠 is the constant energy

13

consumption (dragger, cooling box, etc. ) at use stage.

14

In theory, energy required to melt the polymer can be obtained through the fundaments of

15

thermodynamics, as shown in equation (10):

16

(10)

Emelt = mmeltCp(Tmelt - Tambient)

17

Where mmelt is the mass of polymer melt, it is related to flow velocity and extrusion time; Cp is the

18

specific heat of plastic; Tmelt is the melting temperature of the plastic and Tambient is the ambient

19

temperature. '

20

Efill = ∫pdV = f(p1,p2,v1,v2,xn)

(11)

21

Where p represents the instantaneous pressure at volume increment. p1𝑎𝑛𝑑 p2 are the pressure in inlet

22

and out of extrusion dies, respectively. v1𝑎𝑛𝑑v2 represent flow velocity in inlet and outlet of extrusion

23

dies, respectively. xn is the shape parameters of flow channel.

24

Therefore, the environment impact of use stage is expressed as following:

25

'

2

2

'

EIuse = η(ρmeltπCp(r2 - r1)(Tmelt - Tambient)V2t + f(p1,p2,v1,v2,xn) + Pst)

(12)

26

Where ρmelt is density of plastic melt, and 𝑟2 and 𝑟1 are outer and inner radius of plastic pipe,

27

respectively. Ps is the power of fixed energy consumption equipment. The environment performance of

28

use stage is simplified as function relation of shape parameters of flow channel and processing

29

parameters.

30

Therefore, the EIs in the proposed method can be expressed as following: m

31

EILC = (β + γ)

∑

'02 (ρmLmπ|x n

2

- xn |)m +

1

32

2

2

m

n

1

1

∑∑(δm

M

+ εEpron)n + '

η(ρmeltπCp(r2 - r1)(Tmelt - Tambient)V2t + f(p1,p2,v1,v2,xn) + Pst) 8

(13)

ACCEPTED MANUSCRIPT '

1

EILC = f(xn,xn, p1,p2,v1,v2)

(14)

2

As can be seen in equation (14), the environment impact of extrusion dies is a function of shape

3

variables and processing parameters. Generally, processing parameters (pressure and velocity) are

4

related to shape variables of flow channel. Therefore, the best way to improve environment

5

performance of extrusion dies is to optimize shape variables and to obtain an optimum solution.

6

3.3 Constraint conditions of shape optimization

7

The mechanical performances of extrusion dies are affected by geometry, strength and stiffness. The

8

geometry was constrained within the available physical space, which defines the design variables

9

within a limited scope. Strength of products is the ability to withstand an applied stress without failure.

10

Stiffness which is the ability to withstand an applied load is represented by displacement of extrusion

11

dies. Therefore, to ensure mechanical performance of extrusion dies, stress and displacement should be

12

defined within predefined values. The initial values of stress and displacement are obtained using

13

numerical simulation. So, strength and stiffness constrains are defined as:

{

14

σmax ≤ ασ0 dmax ≤ αd0

(15)

15

Whereσmax and dmax are the maximum stress and displacement of optimized extrusion dies,

16

respectively. σ0 and d0 are the maximum stress and displacement of the original extrusion dies,

17

respectively. α is the coefficient used to balance the relationship between mass reduction and structure

18

performance. It has better behavior in both weight reduction and structure performance while α = 1.2

19

(Xu et al., 2012).

20 21

4 Case study

22

In this section, a model of extrusion dies for plastic cylindrical pipes is developed to demonstrate

23

effectiveness of the proposed method using structural optimization and LCA. The physical structure

24

and 3D model of the extrusion dies are shown in Fig.2, with courtesy from the industrial partner

25

Ningbo FangLi Group Co, Ltd. The function of the extrusion dies weighted 16.5 tons is to deliver a

26

homogeneous molten plastic and produce a continuous pipe of 1000mm diameter. The proposed

27

lightweight design method integrating FEA and LCA is used to realize weight and environmental

28

burden reduction for the extrusion dies.

9

ACCEPTED MANUSCRIPT

Outlet

Extrusion dies

Rack

Heater

Inlet

Head Land Die plate Head (1) transit Head (2) support Color ring Land transit Die land

Outer part Shunt cone Spiral mandel part Inner connectionTransition pin Pin transit Die pin part

1 2 3

(a) Extrusion dies

Flow channel Inner part

(b) 3D model of extrusion dies

Fig. 2 Geometry structure of extrusion dies for producing plastic pipe

4 5

A conventional lightweight design method has been proposed to reduce weight and fulfill its fluid

6

and mechanical performance by the authors (Nie et al., 2015). The first step is to simulate the fluid and

7

mechanical performance of plastic extrusion dies to obtain the constraints for design optimization; and

8

then, the structure of plastic extrusion dies is analyzed to identify boundary conditions of structural

9

optimization process. Thirdly, design criteria is determined to establish optimization model. Finally,

10

the optimized design is solved based on the optimization model, and the results can be obtained by

11

comparing the optimized design with the original one. The procedure of the conventional lightweight

12

design method for plastic extradites was presented as fig.3 (Nie et al., 2015). To model the fluid and mechanical performance of plastic extrudates To identify design parameters and their boundary values To determine design criteria for reaching target values

To solve the optimization structure

13 14

To evaluate the optimized structure comparing with the original one

Fig.3 Procedure of the conventional lightweight design method for plastic extradites

15 16

According to the proposed procedure, the extrusion dies using the conventional lightweight method is

17

obtained, and the comparison between the original extrusion dies and the obtained one is carried out as

18

shown in Table 1. The pressure and velocity of polymer in the original extrusion dies were kept the 10

ACCEPTED MANUSCRIPT 1

same for optimization. The optimization results showed 18.1% of weight reduction yet 7.0% and 6.3%

2

increase in the maximum displacement and stress respectively. It indicates that the conventional

3

lightweight design can reduce the weight of extrusion dies significantly. However, in the previous

4

work, the environmental performance has not been taken into account in the optimization process.

5 6

Table 1 Comparison results of the original extrusion dies and the one with the conventional lightweight

7

design method Polymer pressure (Mpa)

Velocity (mm/s)

Displacement (mm)

Stress (Mpa)

Weight (t)

Original extrusion dies Optimized extrusion dies with conventional method

41.3

19.7

0.0227

58.280

16.55

41.3

19.7

0.0243

61.929

13.56

Difference

0

0

7.0%

6.3%

-18.1%

8 9

In order to overcome the environment burden shift problem of the previous work, environmental

10

performance aspects of extrusion dies have been taken into consideration in this case. Generally,

11

service time of extrusion dies is around 10 years, and extrusion dies are normally replaced after 10

12

years in service. In order to analyze the EIs of extrusion dies throughout the entire life cycle, the

13

functional unit chosen for the case study is 10 years. The following assumptions are made for the

14

modeling: 1) Physical connections among different components of extrusion dies are neglected; 2)

15

Linear environmental evaluation model, which means that EIs can be scaled by a simple multiplication.

16

For example, EIs of 1kg steel are 216mpt, and then 100kg of steel causes 21.6pt EIs; 3) Constant EIs

17

per the unit mass for a specific machining process. For example, the EI value for removing 1kg

18

material by turning is fixed; 4) EIs at material extraction stage are proportional to the mass of raw

19

material; 5) EIs of EOL stage are dependent on its disposal strategy. In the case study, it is assumed the

20

rate of recycled material of extrusion dies is 80% and the rate of incineration material is 20%; 6) The

21

cut-off rule in this case is any component contributing less than 5% to the product’s overall weight is

22

excluded.

23

Different manufacturing processes and extrusion processing data are taken into consideration in the

24

LCA. Life cycle inventory (LCI) was compiled using a series of data sources. The information about

25

the materials, manufacturing processes and extrusion processing data was provided by the industry

26

partner. Data on electricity consumption and weight of extrusion dies are collected and calculated. LCI

27

data for transportation activities, electricity generation, resource generation and disposal and recycle in

28

the background system were obtained from eco-invent database. According to the mathematical model 11

ACCEPTED MANUSCRIPT 1

(as shown in equation (14)) in Section 3, the EIs of different life cycle stages are related to mass and

2

energy consumption of components. Therefore, the LCI analysis is important to the optimization. Table

3

2 shows the material information of different components at material extraction stage. It includes

4

different material types of components and mass information of rough and finished components.

5 6

Table 2 Material information of different components in material extraction stage Components

Material type

Mass of finished components (kg)

Mass of rough components (kg)

Die land Die pin Land support

ZG270-500 ZG270-500 ZG270-500

1605.4 1993.3 388

2638 2979 741

Head (2) Head transit Inner connection body Head (1)

ZG270-500 ZG270-500 ZG270-500 ZG270-500

1909 3069 1094 1410

3128 4266 1742 1999

Die plate Color ring Flange of color ring Transition pin Cooling ring

45# Steel 45# Steel 45# Steel ZG270-500 Q235 40Cr

498 490.7 515.6 1974.1 251.4 716

845 988 1080 2738 438.2 1510

Spiral

7 8

There are four main manufacture processes of these components: casting, forging, turning and drilling.

9

The machining time and the power of machine tools at manufacturing stage are shown in Table 3. The

10

tick in the chart denotes the semi-finished components are formed by casting or forging.

11 12

Table 3 Process information of the extrusion dies at manufacture stage Forgin g

CNC turning(min/kW)

Convention turning (min/kW)

Boring (min/kW)

Drilling (min/kW)

Components

Casting

Die land Die pin

 

580/68 420/68

-

-

470/9.5 150/9.5

Land support



275/68

-

-

167/9.5

Chuck ring Head (2) Head transit Inner connection Head (1) Die plate Color ring Flange of color

    

300/68 1080/68 730/68 480/35 530/35 140/35 420/68 400/68

360/22 480/22 30/22

150/11 270/11

140/9.5 350/9.5 750/9.5 475/9.5 480/9.5 605/9.5 420/9.5 370/9.5

  

12

ACCEPTED MANUSCRIPT

Components

Casting

Forgin g

CNC turning(min/kW)

Convention turning (min/kW)

Boring (min/kW)

Drilling (min/kW)

-

450/22

-

270/9.5

1330/35 1150/25

650/22

-

17/9.5 650/9.5

ring Transition pin Cooling ring Spiral

 

1 2

In the shape optimization of extrusion dies, the definition of design variables is very important for the

3

optimization, leading to change in mechanical performance and environmental performance of

4

extrusion dies. Due to shear thinning behavior of molten plastic caused by its unique material

5

properties, the flow performance is sensitive to changes in flow channel profile of extrusion dies. A

6

small change in the channel shape may cause considerable change of the melt flow behaviors.

7

Therefore, to keep the same quality of the products as these produced by the original dies, the flow

8

performance (flow velocity, outlet pressure, etc.) and the profile of flow channel remain the same for

9

the optimization. The design variables for shape optimization are defined as the inner radius r1,…, r12

10

and external radius R1,…, R12 as shown in Fig.4. By increasing the inner radius and decreasing

11

external radius, the weight of extrusion dies is decreased.

12 13

Fig.4 Shape variables definition of whole extrusion dies

14 15

As mentioned in section 3, the environmental impact evaluation is calculated by Eco-Indicator 99

16

method. According to the Eco-Indicator 99, the impact categories include Carcinogens, Respiratory

17

organics, Respiratory inorganics, Climate change, Radiation, Ozone layer, Ecotoxicity, Acidification,

18

Land use, Minerals and Fossil fuels. Three steps are required to manage these impact categories

19

including characterization, normalization and weighting. The first step is to characterize the impacts

20

categories. The second step is to normalize the characterized impacts categories into three damage

21

categories including Human Health, Resources and Ecosystem Quality. Based on the normalized

22

results, the weighting factors are assigned to estimate the environmental impacts in the weighting step. 13

ACCEPTED MANUSCRIPT 1

The estimated EIs results are regarded as one of optimization objectives in the optimization equations.

2

The optimization models presented in section 3 are employed.

3

Fig.5 demonstrated the optimization procedure of the proposed lightweight method for the extrusion

4

dies. Note that the extrusion dies are simplified as a whole component in the lightweight optimization

5

model, while they are decomposed into different components for environmental impact evaluation.

6

Simapro 8.0 software is used to evaluate EIs, maintaining the same assumption and limitations, the

7

same allocations and impact categories, and the same criteria in the data quality established previously.

8

As shown in Fig.5, by optimizing shape parameters, environmental performance of extrusion dies is

9

improved, while weight of extrusion dies is decreased. But the EIs of some components such as color

10

ring are increased due to increased machining allowance in turning process.

11

12 13

Fig.5 Procedure and optimization results of the proposed lightweight design method

14 15

Two components (Head (1) and Die pin) are taken as examples to demonstrate the statistical analysis

16

for the effects of the shape parameters on the EIs as shown in Fig.6, where the shape parameter R2 is

17

for Head (1) and the shape parameter r11 is for Die pin. The shape parameter R2 has a great effect on

18

Land use, while r11 has more impacts on Ozone layer and Radiation. Fig. 7 presents the comparison

19

for the effects of the shape parameters on the EIs. The EI increases with the increase of the shape

20

parameter R2, while it decreases with the increase of the shape parameter r11 of Die pin. Further, for 14

ACCEPTED MANUSCRIPT 1

Land use and Ozone layer category, the similar effects have also been observed respectively relative to

2

the shape parameters of Head (1) and Die pin.

3 Carcinogens 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

Fossil fuels

Minerals

Resp. organics

Resp. inorganics

Land use

Climate change

Acidification

4 5

Radiation Ecotoxicity

r11(%) R2(%)

Ozone layer

Fig.6 Statistical analysis for the effects of the shape parameters on the environmental impacts

6 12.8

43.87 43.86 43.85 43.84 43.83 43.82

12.75 12.7 12.65 12.6 12.55 12.5

603

7

611

619

627

603

635

611

619

627

635

R2 (mm)

R2(mm)

Environmental impact of Die pin

Ozone layer of Die pin

43.92

105.5

43.91

Impact category (10-3pt)

Total environmental impact (kpt)

8 9

Land use of Head (1) 12.85

43.88

Impact category (pt)

Total environmental impact (kpt)

Environmental impact of Head (1) 43.89

43.9 43.89 43.88 43.87 43.86 43.85

105 104.5 104 103.5 103

43.84 210

216

222

228

210

234

r11(mm)

216

222

228

234

r11(mm)

Fig.7 Comparison for the effects of the shape parameters on the environmental impacts

10 11

Furthermore, Fig.8 presented the results of EI results of each environment category at each life stage

12

for these three extrusion dies: the original extrusion dies, the lightweight extrusion dies with

13

conventional lightweight design, and the redesigned extrusion dies with the proposed method

14

integrating lightweight design tool and LCA. It can be seen that impacts of environment categories

15

vary at each life stage. For example, for the extrusion dies using the lightweight method proposed in

16

this paper, fossil fuels has different values at different life stages, e.g. 12,600 PAF*m2yr at raw

17

material stage, 16,800 PAF*m2yr at manufacturing stage, 117,000 PAF*m2yr at use stage and -7840

18

PAF*m2yr at EOL stage. Furthermore, in comparison with the original extrusion dies, only the value

19

of Land use category is decreased for the extrusion dies with the conventional lightweight method,

15

ACCEPTED MANUSCRIPT 1

while the EIs under other categories are increased. For the extrusion dies using the method proposed in

2

this paper, the EIs of all categories are decreased compared to that for original extrusion dies. Impacts categories Carcinogens Resp. Organic Resp. Inorganic Climate Change Radiation Ozone Layer Eco toxicity Acidification Land use Minerals (MJ Fossil fuels Stage (DALY) (DALY) (DALY) (DALY) (DALY) (DALY) (PAF*m2yr) (PAF*m2yr) (PAF*m2yr) surplus) (PAF*m2yr) Raw material 6.30E-03 7.81E-05 5.54E-02 6.77E-03 2.32E-05 1.74E-06 1.04E+04 525 274 5.36E+03 1.46E+04 Original Manufacturing 0.02 3.28E-05 5.46E-02 9.60E-03 1.03E-04 2.35E-06 7.68E+04 992 122 1.72E+04 2.73E+04 extrusion dies Use 2.97E-03 5.80E-05 0.638 0.116 3.28E-07 1.27E-08 1.04E+05 1.67E+04 0 22.4 1.17E+05 End of Life -3.71E-03 -5.03E-05 -4.25E-02 -6.25E-03 -7.49E-06 -8.54E-07 -4.58E+03 -400 -117 -2.22E+03 -9.03E+03 Total 2.56E-02 1.19E-04 7.06E-01 1.26E-01 1.19E-04 3.25E-06 1.87E+05 1.78E+04 2.79E+02 2.04E+04 1.50E+05

Extrusion dies using traditional lightweight design method

3 4

Extrusion dies using proposed lightweight design method

Carcinogens Resp. Organic Resp. Inorganic Climate Change Radiation Ozone Layer Eco toxicity Acidification Land use Minerals (MJ Fossil fuels (DALY) (DALY) (DALY) (DALY) (DALY) (DALY) (PAF*m2yr) (PAF*m2yr) (PAF*m2yr) surplus) (PAF*m2yr) Raw material 5.16E-03 6.40E-05 4.54E-02 5.54E-03 1.92E-05 1.42E-06 8.51E+03 430 224 4.40E+03 1.19E+04 Manufacturing 2.72E-02 4.28E-05 6.91E-02 1.24E-02 1.36E-04 3.05E-06 9.03E+04 1.27E+03 125 1.95E+04 3.50E+04 Use 2.97E-03 5.80E-05 0.638 0.116 3.28E-07 1.27E-08 1.04E+05 1.67E+04 0 22.4 1.17E+05 End of Life -3.04E-03 -4.12E-05 -3.48E-02 -5.12E-03 -6.13E-06 -6.99E-07 -3.76E+03 -328 -95.8 -1.82E+03 -7.40E+03 Total 3.23E-02 1.24E-04 7.18E-01 1.29E-01 1.49E-04 3.78E-06 1.99E+05 1.81E+04 2.53E+02 2.21E+04 1.57E+05 Stage

Stage Raw material Manufacturing Use End of Life Total

Carcinogens Resp. Organic Resp. Inorganic Climate Change Radiation Ozone Layer Eco toxicity Acidification Land use Minerals (MJ Fossil fuels (DALY) (DALY) (DALY) (DALY) (DALY) (DALY) (PAF*m2yr) (PAF*m2yr) (PAF*m2yr) surplus) (PAF*m2yr) 5.47E-03 6.78E-05 4.81E-02 5.87E-03 2.01E-05 1.51E-06 9.01E+03 456 237 4.65E+03 1.26E+04 1.39E-02 2.09E-05 3.27E-02 6.02E-03 6.72E-05 1.48E-06 3.91E+04 610 43.7 8.05E+03 1.68E+04 2.97E-03 5.80E-05 0.638 0.116 3.28E-07 1.27E-08 1.04E+05 1.67E+04 0 22.4 1.17E+05 -3.22E-03 -4.36E-05 -3.69E-02 -5.42E-03 -6.50E-06 -7.41E-07 -3.98E+03 -347 -101 -1.93E+03 -7.84E+03 1.91E-02 1.03E-04 6.82E-01 1.22E-01 8.11E-05 2.26E-06 1.48E+05 1.74E+04 1.80E+02 1.08E+04 1.39E+05

Fig.8 Environmental impact results of impact categories for three kinds of extrusion dies

5 6

Based on the results in Fig.8, the sensitive revision on impacts categories for the proposed lightweight

7

method in the paper has been made relative to the conventional lightweight method as shown in Table

8

4. The most significant variations, globally, are those concerning the categories of Minerals and

9

Radiation, with the decreases of 113,400 MJ surplus in the first category, and of 6.83*10-5 (DAILY) in

10

the second one. In addition, Table 4 also emphasizes not only the important variation in the categories

11

of Minerals and Radiation, but also the categories of Carcinogens, Resp. Organic, Ozone Layer, Eco

12 13 14

toxicity and Land use. Table 4 Percentage of variation of the extrusion dies using the proposed lightweight method relative to

15

the conventional lightweight method Impact category

Extrusion dies using the proposed lightweight method (%) “-”denotes “reduction”

Carcinogens Resp. Organic Resp. Inorganic Climate Change Radiation Ozone Layer Eco toxicity Acidification Land use Minerals

-40.8 -16.6 -5.0 -4.9 -45.7 -40.2 -25.6 -3.6 -29.0 -51.2

Fossil fuels

-11.5

16 16

ACCEPTED MANUSCRIPT 1

Additionally, two scenarios with different recycling strategies at EOL stage, AS1 (50%of recycled,

2

50% of incinerated) and AS2 (20% of recycled, 80% of incinerated), are considered to discuss the

3

effects of assumptions on EIs. Table 5 shows the EI results of the extrusion dies for the conventional

4

lightweight and the proposed lightweight in the two scenarios. For both of two different assumptions,

5

the values on EIs obtained by the proposed method in the paper are smaller than the ones by the

6

conventional method. So it is seen that the similar results can be obtained by the proposed method with

7

different assumptions at EOL stage.

8 9

Table 5 Comparison results of impacts categories and total environmental impacts in two scenarios

Unit

AS1 Conventional lightweight method 3.31E-02

Proposed method

AS2 Conventional Proposed lightweight lightweight method 3.75E-02 2.14E-02

Carcinogens

DALY

Resp. Organic

DALY

2.11E-04

2.09E-05

2.31E-04

1.34E-04

Resp. Inorganic

DALY

3.65E-02

3.27E-02

8.23E-01

7.05E-01

Climate Change

DALY

6.31E-03

6.02E-03

1.42E-01

1.25E-01

Radiation

DALY

1.01E-04

6.72E-05

1.67E-04

9.99E-05

Ozone Layer

DALY

2.37E-06

1.48E-06

4.58E-06

3.39E-06

Eco toxicity

PAF*m2yr

4.56E+04

3.91E+04

2.31E+05

1.52E+05

Acidification

PAF*m2yr

8.35E+02

6.10E+02

1.89E+04

1.76E+04

Land use

PAF*m2yr

9.61E+01

4.37E+01

3.12E+02

2.56E+02

Minerals

MJ surplus

1.35E+04

8.05E+03

1.43E+04

8.01E+03

Fossil fuels

PAF*m2yr

1.81E+04

1.68E+04

1.68E+05

1.42E+05

Total

Kpt

4.816E+01

4.45E+01

4.89E+01

4.52E+01

2.03E-02

10 11

5 Discussion

12

Based on the above results, the discussion about the effectiveness of the proposed lightweight design

13

method is presented by comparing the original extrusion dies, the lightweight extrusion dies with

14

conventional lightweight design, and the redesigned extrusion dies with the proposed method in this

15

paper as shown in Table 6. The weight of the extrusion dies is reduced from 16.55t to 13.56t through

16

the conventional lightweight method, which shows 18% weight reduction are achieved. But the

17

resultant EIs in entire life cycle are increased from 47.54 kpt to 48.64kpt. It indicates that although the

18

conventional lightweight method without considering EIs can reduce material consumption, it also

19

increases EIs in life cycle. That is to say, the problem on environmental burden shift is caused by the

20

conventional lightweight design method. For the extrusion dies with the proposed method in the paper,

17

ACCEPTED MANUSCRIPT 1

the weight is 14.36 t and EIs are 46.30kpt, which are less than the ones of the original extrusion dies

2

This proved that the proposed method has a contribution to material reduction and EIs in the entire life

3

cycle.

4 5

Table 6 Material weight and environmental impact of three kinds of extrusion die Weight (t)

Environmental impact(kpt)

16.55

47.54

13.56

48.64

14.36

46.30

Original extrusion dies Extrusion dies with conventional lightweight method Extrusion dies with the proposed method

6 7

Furthermore, the breakdown of EIs at the four key stages of life cycle for the three designs of extrusion

8

dies is shown in Fig. 9. It can be seen that though EIs at the materials extraction stage through light

9

weight design are improved, there is 29% increase in EIs at the manufacturing stages using

10

conventional light design method. As a result, 2.3% higher resultant EIs using the conventional light

11

weight design method than that for the original design were observed. This indicates that the improved

12

EIs at the material extraction stage through the conventional lightweight method has been transferred to

13

manufacturing stage. Compared the redesigned products using the proposed method with the one

14

through the conventional lightweight design, although the EIs at material extraction stage with the

15

proposed method are a little higher, significant decrease in EIs from 6.04Kpt to 3.61Kpt were observed

16

at manufacturing stage, and consequently, the total EIs of the redesigned products in life cycle are

17

lower than the one with the conventional lightweight design.

18 19 20

(a) (b)

Fig.9 Comparison of environmental impact evaluation results for three kinds of extrusion dies

21 22

Note that there is a limitation of the proposed method from an aspect of a single stage in life cycle. The

23

proposed method does not work on environmental improvement at the life stages if there is no 18

ACCEPTED MANUSCRIPT 1

environmental burden shift to the life stages caused by the conventional lightweight design. For

2

example, comparing the environmental impacts of the original products with that of the conventional

3

lightweight products in the use stage in Fig.6 (a), the environmental burden for both of them is 39.6kpt.

4

Therefore, the environmental burden for the proposed lightweight method is also 39.6kpt, where there

5

is no environmental improvement in the use stage. The environmental performance in use stage of

6

extrusion dies is affected by the flow channel which is determined based on extrusion process

7

parameters and plastic pipes product parameters. The environmental pollution in use stage can be

8

optimized by further integrating the optimization of process parameters and product parameters into the

9

proposed method.

10 11

6 Conclusions

12

This paper proposed an integrated lightweight design method that combines environmental

13

performance evaluation with shape optimization to prevent environmental burden shift problem caused

14

by conventional lightweight design of extrusion dies. The shape optimization is implemented by using

15

FEA method, and environmental performance evaluation with LCA method is integrated as an

16

objective of the optimization models. Four life cycles including material extract, manufacturing

17

processes, extrusion processing and EOL are taken into account in LCA tool.

18

This study shows that although the conventional lightweight method of extrusion dies without

19

considering EIs can reduce material consumption, it does not always lead to environmental

20

performance improvement in entire life cycle and could potentially lead to environmental burden being

21

shifted from design stage to other life cycle stages. Compared with 18% of weight reduction but 29%

22

increase in EIs at manufacturing stage for the conventional lightweight design, the proposed method in

23

the paper has achieved 13% of weight reduction and 16% reduction in EIs at manufacturing stage. The

24

results indicate that the proposed lightweight design method has great potential to realize weight

25

reduction and meanwhile ensure environmental performance optimization of extrusion dies.

26

The environmental performance evaluation result also indicates that use stage contributes to the total

27

EIs most. It is imperative to reduce EIs at use stage and improve whole environment performance.

28

Further research will focuses on optimization modeling for extrusion process parameters to optimize

29

flow channel of extrusion dies. The EIs at use stage can be re-evaluated by further integrating the

30

optimization of process parameters and product parameters into the proposed method in the paper.

31 32

Acknowledgements

33

The authors would like to thank the support from the National Natural Science Foundation of China 19

ACCEPTED MANUSCRIPT 1

(Grant No. 51605058), Chongqing Research Program of Basic Research and Frontier Technology (No.

2

cstc2015jcyjBX0088), Six talent peaks project in Jiangsu Province (Grant No. 2014-ZBZZ-006),

3

"excellence plans-zijin star" Foundation of Nanjing University of Science and Technology (Grant No.

4

2015-zijin-07), and the industrial partner Ningbo FangLi Group Co, Ltd.

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53

References Andriankaja, H., Vallet, F., Le Duigou, J., Eynard, B. (2015) A method to ecodesign structural parts in the transport sector based on product life cycle management, Journal of Cleaner Production, 94(1), 165-176 Almeida, D. N. F. (2011). Life cycle engineering approach to analyse the performance of biodegradable injection moulding plastics. Mechanical Engineering, Instituto Superior Tecnico Universidade Tecnica de Lisboa: Lisboa. Chen, H., Zhao, G., Zhang, C., Guan, Y., Liu, H., & Kou, F. (2011). Numerical simulation of extrusion process and die structure optimization for a complex aluminum multicavity wallboard of highspeed train. Materials and Manufacturing Processes, 26(12), 1530-1538. Ermolaeva, N. S., Kaveline, K. G., & Spoormaker, J. L. (2002). Materials selection combined with optimal structural design: concept and some results. Materials & design, 23(5), 459-470. Ermolaeva, N. S., Castro, M. B., & Kandachar, P. V. (2004). Materials selection for an automotive structure by integrating structural optimization with environmental impact assessment. Materials & Design, 25(8), 689-698. Fleury, C., & Braibant, V. (1986). Structural optimization: a new dual method using mixed variables. International journal for numerical methods in engineering, 23(3), 409-428. Goedkoop, M. (1999). A damage oriented method for life cycle impact assessment. The Eco-indicator 99. Holloway, L. (1998). Materials selection for optimal environmental impact in mechanical design. Materials & Design, 19(4), 133-143. International Organization for Standardization (ISO), 2006. International Standard ISO 14040: 2006. Environmental Management-Life Cycle Assessment-Principles and Framework, Geneva, Switzerland. International Organization for Standardization (ISO), 2006. International Standard ISO 14044: 2006. Environmental Management - Life Cycle Assessment – Requirements and Guidelines, Geneva, Switzerland. Jin, J. (2010). The Finite Element Method in Electromagnetics. Wiley-IEEE Press. Joost, W. J. (2012). Reducing vehicle weight and improving US energy efficiency using integrated computational materials engineering. Jom, 64(9), 1032-1038. Kostic, M., & Reifschneider, L. (2006). Design of extrusion dies. Encyclopedia of Chemical Processing DOI, 10. Marta Rossi, Michele Germani, Alessandra Zamagni. Review of ecodesign methods and tools. Barriers and strategies for an effective implementation in industrial companies. Journal of Cleaner Production, 2016,129: 361-373 Mattis, J., Sheng, P., DiScipio, W., & Leong, K. (1996, May). A framework for analyzing energy efficient injection-molding die design. In Electronics and the Environment, 1996. ISEE-1996., Proceedings of the 1996 IEEE International Symposium on (pp. 207-212). IEEE. Miller, E., & Rothstein, J. P. (2004). Control of the sharkskin instability in the extrusion of polymer melts using induced temperature gradients. Rheologica acta, 44(2), 160-173. Nie, Y., Lin, Y. J., Sun, W., & Huang, T. (2015). A Methodology for Optimal Lightweight Design of Moulds and Dies: A Case Study. In: ASME 2015 International Mechanical Engineering Congress and Exposition, 13-19 November Texas, ASME, New York. http://dx.doi.org/10.1115/IMECE2015-51039” Pauli, L., Behr, M., & Elgeti, S. (2013). Towards shape optimization of profile extrusion dies with respect to homogeneous die swell. Journal of Non-Newtonian Fluid Mechanics, 200, 79-87. Polavarapu, S., Thompson, L. L., & Grujicic, M. (2009, January). Topology and free size optimization with manufacturing constraints for light weight die cast automotive backrest frame. In ASME 2009 20

ACCEPTED MANUSCRIPT 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43

International Mechanical Engineering Congress and Exposition (pp. 641-655). American Society of Mechanical Engineers. Poulikidou, S., Björklund, A., & Tyskeng, S. (2014). Empirical study on integration of environmental aspects into product development: processes, requirements and the use of tools in vehicle manufacturing companies in Sweden. Journal of Cleaner Production, 81, 34-45. Poulikidou, S., Schneider, C., Björklund, A., Kazemahvazi, S., Wennhage, P., & Zenkert, D. (2015). A material selection approach to evaluate material substitution for minimizing the life cycle environmental impact of vehicles. Materials & Design, 83, 704-712. Russo, D., & Rizzi, C. (2014a). Structural optimization strategies to design green products. Computers in industry, 65(3), 470-479. Russo, D., & Rizzi, C. (2014b). An ECO-DESIGN Approach Based on Structural Optimization in a CAD Framework. Computer-Aided Design and Applications, 11(5), 579-588. Simões, C. L., Pinto, L. M. C., & Bernardo, C. A. (2013). Environmental and economic assessment of a road safety product made with virgin and recycled HDPE: A comparative study. Journal of environmental management, 114, 209-215. Shea, K., & Smith, I. F. (2006). Improving full-scale transmission tower design through topology and shape optimization. Journal of structural engineering, 132(5), 781-790. Strano, M., Monno, M., & Rossi, A. (2013). Optimized design of press frames with respect to energy efficiency. Journal of Cleaner Production, 41, 140-149. Thiriez, A., & Gutowski, T. (2006, May). An environmental analysis of injection molding. In Electronics and the Environment, 2006. Proceedings of the 2006 IEEE International Symposium on (pp. 195-200). IEEE. Wang, M. Y., Wang, X., & Guo, D. (2003). A level set method for structural topology optimization. Computer methods in applied mechanics and engineering, 192(1), 227-246. Witik, R. A., Payet, J., Michaud, V., Ludwig, C., & Månson, J. A. E. (2011). Assessing the life cycle costs and environmental performance of lightweight materials in automobile applications. Composites Part A: Applied Science and Manufacturing, 42(11), 1694-1709. Xu, D., Chen, J., Tang, Y., & Cao, J. (2012). Topology optimization of die weight reduction for highstrength sheet metal stamping. International Journal of Mechanical Sciences, 59(1), 73-82. Yilmaz, O., Gunes, H., & Kirkkopru, K. (2014). Optimization of a profile extrusion die for flow balance. Fibers and Polymers, 15(4), 753-761. Yilmaz, O., Anctil, A., & Karanfil, T. (2015). LCA as a decision support tool for evaluation of best available techniques (BATs) for cleaner production of iron casting. Journal of Cleaner Production, 105, 337-347. Zhang, C., Zhao, G., Guan, Y., Gao, A., Wang, L., & Li, P. (2015). Virtual tryout and optimization of the extrusion die for an aluminum profile with complex cross-sections. The International Journal of Advanced Manufacturing Technology, 78(5-8), 927-937. Zhang, Y., Zhu, P., Chen, G. L., & Lin, Z. Q. (2007). Study on structural lightweight design of automotive front side rail based on response surface method. Journal of Mechanical Design, 129(5), 553-557. Zhang, Y., Liang, K., Li, J., Zhao, C., & Qu, D. (2016). LCA as a decision support tool for evaluating cleaner production schemes in iron making industry. Environmental Progress & Sustainable Energy, 35(1), 195-203.

21