Available online at www.sciencedirect.com
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Procedia CIRP 26 (2015) 229 – 234
Creating an environmentally sustainable food factory: A case study of the
Lighthouse project at Nestlé
J. H. Miah 1,2,, A. Griffiths 1, R. McNeill 3, I. Poonaji 3, R. Martin 3, S. Morse 2, A. Yang 4, J. Sadhukhan 2
1
2
Nestlé UK Ltd, Rowan Drive, Fawdon, Newcastle Upon Tyne, NE3 3TR, UK
Centre for Environmental Strategy (CES), Faculty of Engineering & Physical Sciences, University of Surrey, Guildford, GU2
7XH, UK
3
4
Nestlé UK Ltd, Group Technical, Haxby Road, York, YO91 1XY, UK
Department of Engineering Science, University of Oxford, Parks Road, Oxford, OX1 3PJ
Abstract
Many manufacturing companies recognise the need to produce products that are cleaner, greener, and
environmentally sustainable, yet they are only at the early stages of this transition in addressing the symptoms
of unsustainability at their direct operations by reducing waste and the use of energy, water and material. The
implementation of reductions in these areas can be disparate and minimal given the life cycle of a product.
Bridging the gap between the rhetoric of sustainable manufacturing and reality requires a holistic, systems
thinking approach to ensure the implementation of sustainability is unified and strategic. This paper presents a
novel environmentally sustainable manufacturing framework that encompasses energy, water, waste,
biodiversity, and people & community. It adopts a systems thinking perspective to address the factories
‘environmental life cycle impact to deliver factory and supply chain benefits. The insights from the application
at a Nestlé confectionery factory are reported.
Keywords:
Environmental Sustainability; Sustainable Manufacturing; Life Cycle Analysis; Systems Thinking; Food
Factory; Confectionery
1 INTRODUCTION
In recent years, there has been a growing interest in
‘sustainable manufacturing’ [1-5] as part of the endeavour to
move towards a green and resource-efficient global economy
[6, 7]. The UK’s largest manufacturing sector – the food
industry – is under increasing pressure from regulators,
consumers, and NGOs to ensure they are operating more
sustainable [8-11]. Due to the diversity of food products and
scale of operations (i.e. global to local), the implementation,
pace and principles of sustainable manufacturing in industry
is disparate, uncoordinated and limited in scope. At a system
level, many manufacturing companies operate in complex
business, environmental and social environments (Figure 1).
This requires many actors to ‘act’ in alignment simultaneously
to contribute to a system-level change and therefore
overcome the ‘Prisoners’ Dilemma’ [12]. Although the goal of
a system-level change is desirable and important, many
manufacturing companies are at the early stages of the
transition towards sustainable manufacturing.
The general approach by companies toward sustainable
manufacturing in practice [13-17] has been to focus resource
(e.g. time, people, finance) at direct operations with a limited
impact boundary i.e. factories with an external local/regional
impact level. The common areas that are addressed in an
incremental process to varying degree include; energy, water,
waste, packaging, transport, buildings, employee, community
and supplier engagement. Although innovation is key for
future progress there are general frameworks available to
focus on these areas through the implementation of the
energy, water, and waste hierarchy, and the adoption of
sustainability certification schemes for buildings (e.g.
BREEAM). Also, in recent times, awareness of biodiversity
and ecosystems has risen [18] to the extent some companies
are seeking to demonstrate these considerations within their
operations [17, 19]. However, industrial practices are largely
shaped and subjected to economic models based on neoclassical economic theory. This hinders a fast transition
towards sustainable manufacturing e.g. long paybacks.
In comparison, conceptual sustainable manufacturing themed
frameworks can also vary in scope and breadth from
machine-level [3], facility-level [4] and supply chain-level [5]
and can cover a range of environmental, social and economic
considerations. This can be attributed to the floating signifier
properties of the sustainability dimension and the complexity
of modern manufacturing in its entirety. For example, the
OECD has developed a sustainable manufacturing toolkit [4]
that provides a step-by-step guide for ‘environmental
excellence’ at a facility-level covering; materials, water,
energy, infrastructure, travel and logistics, releases, and
products. However, the toolkit is limited to the facility-level. In
contrast, Duflou et al [20] focuses solely on energy efficiency
but at multiple levels; device/unit, line/cell/multi-machine
system, facility, multi-factory system, enterprise/global supply
chain. In a similar manner, Jayal et al [5] advocates a
sustainable manufacturing framework that takes a holistic and
multiple view of manufacturing that involves the entire supply
chain centred on product innovation via Design for
Environment (DfE). Therefore, taken together, the picture for
sustainable manufacturing is broad and challenging to
implement in practice, given the complex business,
environmental and social environment of manufacturing
(Figure 1).
A recent trend in industry as an approach to setting the pace
towards sustainable manufacturing is to establish
sustainability pilot projects (Table 1) that will act as a beacon
or a ‘Lighthouse’ for encouraging comparatively high
sustainability performance across a company’s multiple
manufacturing sites. The alternative approach – i.e. top-down
The Global Conference on Sustainable Manufacturing
2212-8271 © 2015 Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/3.0/).
Peer-review under responsibility of Assembly Technology and Factory Management/Technische Universität Berlin.
doi:10.1016/j.procir.2014.07.030
230
J.H. Miah et al. / Procedia CIRP 26 (2015) 229 – 234
– is to decide how to strategically select sites for specific
solutions; this often results in a series of feasibility studies
and often ends in delayed action or no action – i.e. paralysis
by analysis. The bottom-up approach is an alternative to the
top-down approach as it provides flexibility and freedom for a
site. It enables more accelerated development, as bottom-up
practical and workable solutions then establish a site with
high sustainability performance. The main benefit of the pilot
approach is that it enables a company to test in the context of
sustainable manufacturing; ideas, technologies, and technical
& social processes outside of the organisational mainstream
before scaling-up and rolling-out across the multiple-sites of a
company’s operations.
To this end, this paper provides a short overview of the role of
pilot projects with a sustainability remit and is supported by a
selected case study of the application of a novel
environmentally sustainable manufacturing framework. This
case study is called the ‘Lighthouse Model’ (Figure 2) by
Nestlé UK Ltd and covers energy and Life Cycle Assessment.
The aim of the framework is to further drive the transition
towards sustainable manufacturing by demonstrating the
practical implementation at a confectionery factory that will
act as a blueprint for other manufacturing sites within the
Nestlé factory network and wider industry.
2
THE
ROLE
SUSTAINABILITY
OF
PILOT
INITIATIVES
AND
In the Multi-Level Perspective (MLP) discourse [21, 22] the
role of pilot projects, technologies, grassroots movements are
critical to the Niche (micro) level in bringing about higher
changes at the Regime (Meso) and the Landscape (Macro)
level; a three-level system for transformative change.
The Niche level or ‘area’ is the protected space provided for
radical innovation and experimentation e.g. electric cars, ecodesign, and renewable technologies. This level is less subject
to market/organisational and regulation influences and can
facilitate the interactions between actors that support wider
adoption. The Regime (Meso) level refers to the dominant
practices, rules and technologies that provide stability and
reinforcement to the prevailing socio-technical systems. The
Landscape (Macro) level refers to the overall socio-technical
setting that encompasses both the intangible aspects of
social values, political beliefs and world views and the
tangible facets of the built environment including institutions
and the functions of the marketplace such as prices, costs,
trade patterns and incomes. [21, 22]
In the context of MLP theory, the implementation of
sustainability pilot projects by different companies (Table 1)
seeks to bring about a new way of thinking – mainly internally
to the company, but also the wider industry and society. This
can come from learning-by-doing, expectation formation and
collective impact.
Table 1: Different sustainability-themed pilot initiatives by
manufacturing companies.
Company
Project title / aim
Frito-Lay [23]
Near net-zero manufacturing facility
Ecover [24]
Ecological factory
Arla Foods [25]
Zero-carbon dairy plant
MAS Intimiates Thurulie [26]
Eco-factory
Renault-Nissan [27]
Zero-carbon car factory
Nestlé UK Ltd [28]
Lighthouse Model
3 ASPECTS OF THE STUDY
3.1 Energy efficiency
The rise in industrial energy prices over the past decade [29]
and interest in environmental sustainability has seen many
food manufacturers – the largest manufacturing sector in the
UK - focusing on energy reduction as a top priority [8]. The
food industry, with 9,340 food factories in the UK, is a major
energy user accounting for about 14% of energy consumption
by UK businesses [11, 30]. While this represents a rather
significant proportion of industrial energy use, improving the
energy efficiency of food factories can be a complicated
endeavour given the diversity of the food products
manufactured and the technologies employed.
There are various options open to food processing factories
via the energy hierarchy; energy reduction, energy efficiency
and renewable energy. As part of improving energy efficiency,
heat recovery by heat integration known as Pinch analysis
[31, 32] is another key measure that can be implemented by a
combination of direct and indirect approaches. A common
approach in the practice of Pinch analysis is based on the use
of graphical techniques for carrying out Pinch analysis and
design, which are often applied for targeted areas in a factory
that focuses on either direct or indirect heat exchange by first
building the data bottom-up at a process-level; several heat
integration studies have demonstrated energy savings of 1045% from process retrofitting [32-34].
Despite these achievements, the food processing industry
has not been forthcoming to use such an approach, either at
a targeted area or factory level primarily due to the low
financial returns that can be gained from capturing low grade
heat (typically 50-140°C), diverse thermodynamic profiles,
material quality, non-continuous operation, small number of
streams, integration complexity and seasonal operation [34].
While acknowledging these challenges, there are nonetheless
significant opportunities for the food processing industry to
improve energy efficiency, reduce costs and emissions and
optimise heat recovery systems by applying heat integration
as a retrofit for mature factories. The key results of the
application of a novel heat integration framework developed
by Miah et al [35] are reported in this paper as part of the
‘Lighthouse Model’ (Figure 2).
3.2 Life Cycle Assessment (LCA)
Life Cycle Assessment (LCA) is a system analysis tool to
describe the ‘cradle-to-grave’ environmental impacts of
products and processes [36]. It is an advanced sustainability
tool that powerfully captures the environmental impacts at
different levels e.g. short, mid and long-term. The key benefits
to industry include; environmental hot-spot analysis, product
design & product improvement, strategic planning, supply
chain management, marketing & communications, industrial
ecology and industrial symbiosis.
Recent developments in the LCA landscape for example the
Product Environmental Footprinting (PEF) guidelines [37],
World Food LCA Database [38], and ISO 14000 series
updates [39] has positioned LCA after nearly 40 years since
conception as a key sustainability tool for industry. However,
the general methodology of LCA seems straightforward in
principle but can be challenging and complex in reality where
the company product portfolio is many and diverse e.g.
thousands of product types across different product
categories. This situation is characteristic in the food industry,
due to changing consumer demand, competition and brand
differentiation, thus a portfolio of products via creative-
J.H. Miah et al. / Procedia CIRP 26 (2015) 229 – 234
destructive process is in constant flux (Figure 1). This poses a
major practical challenge for factories and the overall
company aspiring towards environmental sustainability. One
approach to rationalise this complexity and understand key
environmental hot spots across the value chain is to develop
specific methodologies and rules for product categories e.g.
coffee, dairy, confectionery [40]. The challenges associated
with the application of LCA for environmental hot spotting of
confectionery value chains are reported in this paper as part
of the ‘Lighthouse Model’ (Figure 2).
Figure 1: The life cycle of a food product at a system level.
4 METHODOLOGY
The Lighthouse Model (Figure 2) is a six-pillar approach to
sustainable
manufacturing
encompassing
technical,
environmental, economic and social aspects at a regional
level. The difference between the Lighthouse Model and other
pilot projects (Table 1) is the breadth of focus areas that
includes biodiversity and Life Cycle Assessment. The scale of
implementation is principally at a factory level but also
extends to a regional and supply chain level on specific areas
like biodiversity, people & community and value chain. The
different implementation levels are due to the practical level
and reach that a factory can influence externally. For
example, the role of LCA is principally to identify
environmental hot spots across the value chain which can
inform both the factory and company to develop strategic
environmental partnerships with major actors across the
value chain.
To address the different pillars a basic implementation
methodology is first employed followed by further detailed
investigation and research for each pillar. This involves:
1. Create a factory-level sustainability team.
2. Create an internal Lighthouse steering committee to
accelerate decision making and review at a company
level meeting every quarter.
3. Identify internal & external stakeholders on different
pillars.
4. Engage with internal & external stakeholders by seeking
advice and exploring different solutions for the different
pillars.
5. Develop solutions into project proposals.
6. Present projects to Lighthouse steering committee to
prioritise and approve.
7. Implement project.
8. Report full/partial results to Lighthouse steering
committee every quarter.
9. Repeat steps 3 – 8.
Within each pillar, a specific line of research can be explored
to identify further opportunities and solutions. The general
research methodology involves:
1.
2.
3.
4.
Literature review.
Identify gaps in literature and opportunity.
Develop novel methodology and solution.
Present solution to Lighthouse steering committee to
prioritise and approve.
5. Implement project.
6. Report full/partial results to Lighthouse steering
committee every quarter.
7. Repeat steps 1 – 6.
Figure 2: Six-pillar Lighthouse Model and aims.
Since sustainability is an ambiguous term, the search for
sustainable manufacturing is open-ended. As such, the
Lighthouse Model process can continue until the Lighthouse
steering committee are satisfied with the overall achievement.
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J.H. Miah et al. / Procedia CIRP 26 (2015) 229 – 234
5 CASE STUDY
The case studies is a selection of research projects that looks
at maximising energy efficiency by heat integration and the
role of LCA in environmental hot spotting of confectionery
products. Due to the content and scope limitations of this
paper, it is not possible to present full methodologies and
results, and the reader is referred to supporting literature
where available.
5.1 Confectionery factory description
The site used for this case study is a confectionery factory in
the UK that manufactures 13 different brand products that are
sugar, chocolate and biscuit based, and utilises a diverse
range of processing technologies. The 13 brand products are
split across 130 Stock Keeping Units (SKUs) which are a
variation of a brand product format e.g. single bar pack and
multiple bars pack. The factory is over 50 years old and
occupies a large footprint in an urban area with multiple
dedicated production plants (zones) all housed in one
building. The factory is physically constrained by the
presence of housing, transport infrastructure and other
industrial sites. In addition to the range of production zones
there are a number of utility systems that support these
production zones. The factory employs 650 people working in
a number of shifts where the primary activity can vary from
running production (ramp-up and continuous) to cleaning and
maintenance. This is different for different zones and
contributes to the discontinuous nature at a factory level.
5.2 Energy efficiency key results and discussion
The key results and findings of the application of a novel
decision-making framework for heat integration in complex
and diverse food factories are presented [35]. The aim of the
framework is to provide the user with a step-by-step guide to
evaluate all heat recovery opportunities through a
combination of direct and indirect heat integration. The key
features that distinguish this approach from previous authors
[32-34] are the practical holistic assessment of heat
integration from a combination of direct and indirect heat
exchange at both a zonal-level and a factory-level. The whole
procedure comprises four stages; process zoning and data
extraction, preliminary analysis, intra-zonal integration, and
inter-zonal integration. By adopting an integrated approach,
the framework seeks to maximise heat recovery for the total
factory, as opposed to solely for targeted areas which focus
either on direct or indirect heat integration as found in
previous examples [32, 33]. Also, the inclusion of key
decision events that cover potential energy reduction,
material quality, and investment requirement ensure the
assessment is rigorous and justified.
The application of the framework at a confectionery factory in
the UK has resulted in the development of five heat
integration opportunities that collectively can deliver between
3.77–5.72% energy reduction at a factory level with a total
investment of £321,328 and an annual cost saving between
£48,884 – £104,661 resulting in a payback of the cost of the
changes between 3.07 – 6.57 years. The expected energy
savings is on the lower end as it was initially found that the
potential factory energy reduction could be between 13.37–
16.61%. It was found that this factory had a larger heat sink
that could not be matched by the smaller heat source
available. Also, the entire heat source available was not
integrated and the final assessment resulted in a number of
unmatched streams that left the factory with a surplus heat
and a number of unmatched cold sinks that could not be
integrated due to lack of suitable streams, unfavourable
geographical proximity, and potential compromise of material
quality. This surplus heat was found to represent between
9.60-10.89% of the factory energy with a larger cold sink
unmatched representing between 32 – 33.05% of the factory
energy. This amount was unexpected and may be
experienced at other food factories. At this stage, a factory
energy reduction between 3.77 – 5.72% is the highest
amount of what is achievable for this case site with heat
integration. Therefore, other energy reduction measures must
be explored at the unit operation level, such as energy
efficient technologies, behaviour change that encourage
efficient operation of machines, and redesign of production
lines that can contribute to a factory energy reduction.
5.3 Life Cycle Assessment (LCA) key challenges and
discussion
The research for the LCA as part of the Lighthouse Model is
not yet complete and an overview of the goal, scope and
implementation challenges to date are provided.
5.3.1 Goal and Scope:
The scope of the LCA research is from cradle-to-cradle i.e.
full confectionery value chain. The goal is as follows:
1.
2.
3.
Evaluate the practical challenges of implementing LCA
from a factory-level perspective.
Identify
environmental
hot
spots
across
the
confectionery value chain from a factory-level
perspective.
Develop a general LCA methodology for confectionery
products
5.3.2 Functional Unit:
The functional unit is 1000 kg of packaged product.
5.3.3 LCA challenges:
A general attitude in industry [5, 41] is that conducting an LCA
is time-consuming and not practical. Hence, the reluctance for
wide application. However, this is dependent on the sector
and product type e.g. conducting an LCA on a jet engine that
has 10,000 components compared to a food product that has
less than 20 ingredients. The most significant challenge with
LCA lies in data comprehension, availability and reliability. In
the context of the food industry, the diversity of food products
across different product categories e.g. hundreds of
thousands of products sold to consumers compounds the
LCA implementation challenge for a company. From a
factory-level perspective, food factories can manufacture a
range of products in different product formats known as Stock
Keeping Units (SKUs). A SKU is created for new products
and brand extensions and can be in the form of new
packaging material and/or different product size. As a result
of the dynamic food retail environment, the portfolio of SKUs
changes as companies try to appease a changing consumer
palate. The approach to rationalise SKU diversity and develop
a product subject that is representative is to group similar
SKU products e.g. sugar, chocolate and biscuit that share
similar processing technology and where the core product is
similar. This is followed by a packaged volume comparison of
the different product types within a group for a 1 year period.
The highest product type is then selected for the LCA. From
this, each product group contains a number of SKUs which
are sold to a range of customers in different countries.
For the selected product group, there will be a range of
ingredients and packaging materials that are sourced from
various locations and in different quantities with multiple
suppliers e.g. UK, Brazil, and China. The challenge here lies
in rationalising the multiple suppliers to one for each
J.H. Miah et al. / Procedia CIRP 26 (2015) 229 – 234
ingredient and packaging material for environmental hot
spotting. The approach taken was to determine the quantity of
ingredients and packaging materials as a weight % of final
product. This was done by extracting data from the product
specification and recipe. Based on the weight % list, it will
become apparent what the significant materials are and can
be based on the Pareto principle. The approach taken to
justify the selection of one supplier is to compare the volume
of material purchased from each supplier and then select the
highest. Once the LCA model is developed, it would be
possible to change the supplier location parameter to
determine the environmental impact sensitivity.
For the selected product group, there will be a range of SKUs
which have various destinations e.g. domestic or export
markets. Within these markets there can be various
customers e.g. retailers and wholesalers. The challenge here
lies in rationalising the customer destination for environmental
hot spotting. This can be resolved by comparing the SKU
volume and select the significant SKUs based on the Pareto
principle. From this, the significant SKUs are then grouped
based on similar formats e.g. tube packaged product or
bagged packaged product. The highest volume group is then
selected for further analysis. This involves determining the
logistical routes from the factory to the customer destination
based on delivery order data. From the factory, a product will
typically be stored in distribution centres before they are
delivered to a customer. For a national company, there may
be several distribution centres to be able to have a national
reach. From the delivery order data, the delivery volume is
compared for each customer and the significant customers
are identified via the Pareto principle. At this stage, it is up to
the company to decide which customer to select for the LCA
as this can lead to environmental partnerships. Also, once the
LCA model is developed, it would be possible to change the
customer location parameter to determine the environmental
impact sensitivity.
Another challenge which constrains LCA is available Life
Cycle Inventory (LCI) datasets. The largest and widely utilised
database is EcoInvent [42]. However, even this database is
limited and will not contain environmental profiles for all
ingredients in a company product portfolio. Similarly, another
database is the World Food LCA Database [38] which is
currently under development. Therefore, it is unlikely a food
LCA will be able to obtain all LCI data for the different
ingredients given the diversity of food products in the world.
The approach taken to overcome this data gap for
environmental hot spotting is to identify significant ingredients
based on the Pareto principle and then search LCI databases
for relevant environmental profiles. If the profiles are not
available, then direct engagement with suppliers is pursued.
This route opens up a collaborative approach where the
company and supplier seek to work together to understand
environmental impacts and can result in environmental
partnerships.
Another challenge which is woven throughout the
implementation is the handling and reconfiguring of data from
multiple sources e.g. metered, archived, different IT platforms,
CAD, production data measured in tons but delivered data
measured in cases, inconsistent information from people.
There is no simple approach to overcome this as data are
generated and stored in their current manner for a specific
purpose and the link to LCA is an afterthought which will
require further integration. The experience of the LCA
practitioner is important and some of the rules mentioned will
help.
6 SUMMARY
This paper presents an overview of a novel environmentally
sustainable manufacturing framework, supported by a
selected case study from its application at a confectionery
factory in the UK. The case study has involved exploring the
role of Pinch analysis in food factories in maximising energy
efficiency and the implementation challenges of LCA for
environmental hot spotting.
7 ACKNOWLEDGEMENTS
We wish to gratefully acknowledge and thank the EPSRC and
Nestlé UK Ltd for their assistance and support in funding this
research.
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