The new conceptual framework for food supply chain assessment

Journal of Food Engineering 115 (2013) 251–263

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Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng

The new conceptual framework for food supply chain assessment Riccardo Manzini ⇑, Riccardo Accorsi Department of Industrial Engineering, Alma Mater Studiorum - Bologna University, Viale Risorgimento 2, 40136 Bologna, Italy

a r t i c l e

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Article history: Received 19 June 2012 Received in revised form 30 September 2012 Accepted 15 October 2012 Available online 26 October 2012 Keywords: Logistics Food quality Food safety Efficiency Sustainability Horizon 2020 framework programme Made in Italy

a b s t r a c t Food industry is the first in European Community for revenues, with more than 8 millions of employee. Logistics and supply chain management play a crucial role in food industry. This paper presents a general and conceptual framework for the assessment of food supply chain (FSC) and logistics of food products in agreement with a multidisciplinary and integrated view. The target of the proposed integrated approach to supply chain design and management is the simultaneous control of quality (1), safety (2), sustainability (3) and logistics efficiency (4) of food products and processes along the whole FSC ‘‘from farm to fork’’. A case study focused on package design, distribution issues, and supported by the development of an original close-loop control system is a first exemplifying step towards a new integrated approach on FSC assessment in agreement with the proposed conceptual framework. Finally, the paper presents a discussion on the most important challenges in FSC for public and private research in industry and in academic institutions. Ó 2012 Elsevier Ltd. All rights reserved.

1. Introduction The food industry is composed of companies dedicated to manufacturing and processing/transformation of raw materials and semi-finished products coming from primary activities such as agriculture, zootechnics, forestry and fishing. Logistics and operations support this transformation. Food industry accounts for 2% of European GDP and 13.5% of total employment in EU manufacturing sector (Federalimentare, 2012). Food industry is the first one in Europe and the second in Italy for revenues. European food industry is made of about 310,000 companies of which 99% are small and medium sized enterprises (SME). The food sector plays a vital role to satisfy the needs of consumers and contributes annually more than 600 billion Euros to the EU economy. The number of employees amounts to 4.3 millions in EU (Federalimentare, 2012). Italy plays a special role as ambassador of Made in Italy. Italian food industry exports about 23 billion Euros per year and is made of 32,300 companies (6500 with more than 9 employees). It counts about 405,000 employees (Federalimentare, 2012). The most important areas are wine and musts (20%), sweets and bakery products (12.3%), dairy (8.1%), oils and fats (7%), fishery products (1.2%). In Italy, PDO (Protected Designation of Origin) and PGI (Protected Geographical Indication) food products generates 11.5 billion of Euros of revenues, which is about 9.3% of the total revenues. Three billion of 11.5 are due to export. ⇑ Corresponding author. E-mail address: [email protected] (R. Manzini). 0260-8774/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jfoodeng.2012.10.026

In order to support the complete FSC analysis, evaluation, design, planning, management and control, it is necessary to define a set of key performance indicators (KPI). These can be classified in agreement with: 1. the target assessment (e.g. safety, quality, sustainability and eco-efficiency), 2. the step of the supply system involved (e.g. raw materials acquisition, fulfilment, warehousing, manufacturing, distribution), 3. the stakeholders involved (e.g. consumers, logistic provider, manufacturer), 4. the disciplines of interest (e.g. food processing, manufacturing, logistics, microbiology, packaging). A brief description of such classification of impacts and indicators follows. Firstly, the target of the metric represents the area of impacts of the phenomenon to be measured. This manuscript mainly focuses on 4 macro-area of impact involving food products and related activities: food quality and safety, costs efficiency and environmental sustainability. The level of the supply chain (SC) refers to the stage or the activity involved by the analysis or the phenomenon to study, throughout the whole path leading the products from the field to the consumer’s table. The stakeholders of the process are the partners of the chain whose needs are complied by the analysis, and finally the disciplines of interest represent the main research majors, which hold the proper knowledge to face such particular issue. This paper presents an original conceptual framework for the identification and classification of main issues, problems, and

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decisions on SC systems in agri-food industry and sector. This framework supports the identification of the challenges for future public and private research with a special focus on integration in agreement with the final target of a new and effective FSC assessment: the simultaneous control of quality, safety, sustainability and efficiency. A case study on monitoring and simulating the physical and environmental stress conditions of shipments of food products is illustrated as the first effective basis for a closed-loop and simultaneous control along the whole chain from ‘‘farm to fork’’. This exemplifying case study demonstrates the effectiveness of an integrated approach to FSC assessment as proposed by this study. The remainder of this paper is organized as follows. Section 2 presents a literature review and the state of the art on the most critical issues and modeling approach in FSC. Section 3 presents the previously cited main targets of the design, planning, management and control of an integrated FSC: quality, safety, sustainability and efficiency. Section 4 illustrates the proposed conceptual framework for the FSC assessment. Section 5 presents a case study in agreement with the proposed framework. Finally, Section 6 discusses about conclusions and further research. 2. Review of the literature This section overviews and summarizes the state of art of the main aspects and topics of interest on FSC and logistics in food industry. This is not an exhaustive review of the literature. The aim of this section is the classification and illustration of the basic pillars included in the conceptual framework proposed by this paper. A framework for supply chain management (SCM) as the basis for the following discussion and the illustration of the original contributions is presented by Lambert and Cooper (2000). Gunasekaran and Ngai (2012) present an analysis of the future issues in supply chain operations management. In particular, they identify and discuss the emerging operations approaches (e.g. sustainability, partnership and collaboration, integrated technologies as radio frequency identification – RFID, multi-plant operations, etc.), the related decisions, and the research and management science models. Both contributions do not explicitly focus on food FSC. The list of issues and research topics presented in this section is: some quality and safety risk in FSC (1), FSC strategy, collaboration, planning and management (2), food distribution networks (3), sustainable FSC (4), food packaging (5), technologies and tools for FSC assessment (6). This list proposes many topics and related impacts and the influences on food supply chain aspects, processes and partners. 2.1. Quality and safety risk in FSC Supply chains are usually not designed in agreement with a risk evaluation and assessment, although one of the most critical issues is the ‘‘management of risk’’. In FSC, where risk factors may threaten food product quality and safety and thus customers’ health, risks are much less tolerable (Marucheck et al., 2011). In order to assess quality and safety risks in FSC, a very critical need is the prediction of food degradation processes (Labuza, 1982; Man and Jones, 1994; Siracusa et al., 2008). Typically, next to biological variations, food quality is determined by time and environmental conditions, which may be influenced by the type of packaging, way of loading, and the availability of temperaturecontrolled packages, vehicles and warehouses and generally by the complete factors which mainly configure the SC. The quality and nutritional characteristics of raw materials and food products may be altered along the FSC with respect to several

physical factors of stress such as temperature, light, humidity, mechanical static and dynamic stresses (Singh and Singh, 2005). The chemical deterioration of food is caused by adverse reactions (e.g. oxidation) that affect sensitive components such as polyphenols, fats, vitamins and flavorings (Xia and Sun, 2002), with negative consequences on the quality of food products, e.g. wine (Boulton et al., 1996), edible oils and cheeses (Fox et al., 2004; Goff and Hill, 1993), and bakery products (Calligaris et al., 2007). In particular, temperature can significantly affect food products and their shelf life as discussed by Valli et al. (2011) and Frankel (1991). Furthermore, literature presents several contributions on the damage caused by static and dynamic mechanical stresses on selected foods such as fruits and vegetables (Singh and Singh, 1992) and eggs (Berardinelli et al., 2003a). These damages are influenced by the following factors: the type of packaging (Singh and Xu, 1993), the mechanical properties of food products (Berardinelli et al., 2006), the type of transport vehicles and the position of products inside the vehicle (Barchi et al., 2002), and finally the conditions of the ‘‘road surface’’ (Berardinelli et al., 2003b). 2.2. Food supply chain strategy, collaboration, planning and management The new rules of global competition force companies to build, through collaborative relationships with suppliers and customers, a SC strategy to create competitive advantage for the entire SC (Christopher and Holweg, 2011) in terms of quality, efficiency, sustainability and safety. The choice of the proper SC strategy to adopt depend on the product/service and uncertainty of customer demand (Fischer, 1997) as well as the degree of vertical and horizontal integration within the SC (Holweg et al., 2005; Singh and Power, 2009). A recent discussion on SC integration and performance is presented by Prajogo and Olhager (2012). Literature does not yet proposed significant contributions on SC strategy definition, SC integration and SC collaboration in food industry and FSC. Supply chain planning is a supporting decision-making process whose aim is to take the best decisions according to the objectives of planners (Fleischmann et al., 2005). Main processes and decisions are: procurement, production planning and scheduling, demand management and forecasting, inventory control, customers demand allocation, simultaneous facility location and demand allocation (the so-called location-allocation decisions), transport planning, etc. (Beamon, 1998; Li et al., 2006; Dreyer et al., 2009; Manzini and Gebennini, 2008; Manzini and Bindi, 2009; Viau et al., 2009; Manzini et al., 2011; Manzini, 2012a). A comprehensive review of planning models in the agri-food SC is provided by Ahumada and Villalobos (2009). They classify the planning models according to relevant features such as the adopted optimization approaches, the type of involved processes and the scope of the planning activities. The use of integrated planning approaches and models in FSC is still very limited, especially for fresh products since existing literature models fail to incorporate realistic features, such as the shelf-life peculiarities. The typical issues involving SCM are the analysis, design and control of integrated logistic architectures. Supporting-decision methods and mathematical models can be adopted to tackle strategic issues (such as the proper site of the manufacturing facilities or the distribution centers), tactical issues (e.g. the determination of the flows of materials moved within the system and fulfilment decisions), and/or operational issues (e.g. vehicle routing and delivery scheduling, as well as material handling and inventory) (Manzini, 2012a). In FSC such decisions must handled and addressed as quicker as possible since their consequences affect not only costs, but the level of quality of products and processes, the level of sustainability and safety of the supply system with a direct and indirect impacts and consumers safety, health and well-being. Consequently, it is

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necessary to discuss about quality, safety, sustainability and efficiency of the whole SC, including quality and safety of food products. In order to respond to customers’, enterprises’ and institutions’ requirements in terms of health and safety of products and processes, quality certification, economical and environmental sustainable systems, and costs optimization, a complete and integrated study and analysis of FSC infrastructures is necessary. The main objective of a similar analysis is to lead food products from the raw material harvest process to the final consumer throughout the SC. A not exhaustive list of decisions concerning with the design and management of a FSC includes the definition of the most efficient distribution network, the proper design of DCs and warehouse operations, the design and control of manufacturing and processing facilities, the management of cold chain and, finally, the design and development of the reverse logistics network. 2.3. Food distribution networks Researchers have focused relatively early on the design of distribution systems considering the SC as a whole. Recent and comprehensive overview of models and approaches for the analysis of a distribution network are summarized in Melo et al. (2009), Alumur et al. (2008) and Nagy and Salhi (2007). They do not discuss of food industry and FSC. Research seeks to respond to distribution architecture focusing on several main aspects of the problem: the facility location problem (FLP), the allocation problem and the vehicle routing problem (VRP). Several mixed-integer linear programming (MILP) models have been proposed to suggest the proper location of facilities and warehouses according to different constraints and hypotheses (Manzini, 2012a,b). A few examples are the uncapacitated (UFLP) or capacitated location problems (CFLP), single and multi-period location problems. In order to achieve an overall optimal and integrated solution to the configuration of a distribution network, FLP are faced combined with another critical aspect: the allocation of each supplier to a set of points of demand or customers by the so-called location-allocation problem (LAP) modeling. The strategic planning of the proper site of food processing facilities, regional and local DCs, in accordance with the geographical population density, might reduce transportation costs, inventory costs throughout the chain and link raw material and consumers in a sustainable way. Yu and Wang (2006) and Bosona et al. (2011) discuss a few examples. Increasingly, several countries throughout the world are recognizing the importance of both reducing the environmental impacts of their operations and applying optimization techniques (Beamon, 1999; Farahai et al., 2010). Operational scheduling and fleet routing problem in a distribution network can be approached through a wide set of models (Manzini et al., 2008; Manzini and Bindi, 2009; Manzini, 2012a) considering multiple time windows, as instance the product shelf-life, and load capacity constraints aimed to minimize the total traveling and related costs due to delivery missions. The operational planning is particularly critical for perishable products and temporal constraints can significantly reduce the feasibility of such complex decisional problem (Chen and Che-Fu Chang, 2009; Osvald et al., 2008; Hsu et al., 2007). Further contributions on operational issues in distribution planning are organically summarized in a few recent studies (Manzini et al., 2008, 2011a; Manzini, 2012a,b; Gebennini et al., 2009). As crucial nodes of a distribution network, warehouses and DCs are among the main source of inefficiency, waste and uncontrolled costs throughout the SC. Therefore, several literature contributions face the critical issues of warehouse design and management with

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the aim to minimize the operative costs and time. Comprehensive reviews are presented by Gu et al. (2007) and De Koster et al. (2007). The two main leverages and issues in warehousing systems are the design, involving layout and structural patterns specifically devoted to food products, and the operations, dealing with the problem of allocation, assignment, routing, etc. (Gu et al. 2007). Complete overviews on methods and models to respond to warehousing systems criticalities are summarized in Manzini (2012b) and Bartholdi and Hackman (2011). Nevertheless, in FSC the object of time efficiency and cost minimization are joined by more crucial requirements in term of quality and safety of products. Indeed, the impacts of space and time efficiency in warehouse inbound and outbound operations affect the management of fresh or perishables products requiring particular activities and handling approaches (i.e. First-Expiring-First-Out policy, climate-controlled storage). Examples of how warehouse management efficacy and efficiency are achieved in food DCs are presented by Gopakumar et al. (2008) and Di et al. (2011). 2.4. Sustainable food supply chain Carter and Easton (2011) present a systematic review of the literature on sustainable supply chain management (SSCM). They analyze the evolution of the SCM from a so-called ‘‘standalone’’ approach to a corporate social responsibility (CSR)-based approach. They demonstrate that it is necessary to develop models and decision support systems intersecting environmental and/or social performance, and economic performance. Apaiah et al. (2005) presents a first approach to the development and application of a methodology enable to look at quality and environmental loads in FSC. Apaiah et al. (2006) explore the potential of using an analysis of energy requirements to study and compare the environmental impact of FSCs. Further significant contributions on agri-food industry combined with SSCM are recently proposed by the literature (Green, 2010; Gupta and Palsule-Desai, 2011; Chaabane et al., 2012). A sustainable FSC encompasses manufacturing systems and processing issues. It is responsible of processing raw materials into final products, as well managing recovery systems enabling all the post-life treatments. Consequently, in sustainable SCs the reverse logistics (RL) plays a significant role. RL refers to the distribution activities involved in food-packaging returns, source reduction/ conservation, recycling, substitution, reuse, disposal, refurbishment, repairing. The return flow of materials involves the collection activity of products/packages at collection centers or retail outlets, the transfer and consolidation at centralize DCs, and finally the recovery of return products/packages (Accorsi et al., 2011; Das and Chowdhury, 2012). Since for perishable food products the life cycle ends with the consumption, the reverse logistics system in FSC tackles the main issue of packaging collection, consolidation and recycling. A classification of different configurations of RL is illustrated by Min et al. (2006) and Rogers and Tibben-Lembke (1999). Several recent contributions discuss the critical design, planning, management and optimization of complex and reverse logistic networks (Jayaraman and Luo, 2007). Aimed to gain competitive advantage and sustainable development of the entire SC, literature presents models and techniques (Gamberini et al. 2010; Das and Chowdhury, 2012), as well as integrated top-down supportdecision systems for RL (Manzini et al., 2011c). Although literature does not yet present significant contributions on SSCM in agri-food industry, there are many studies on life cycle assessment (LCA) applied to food chain products and processes (Roy et al., 2009; Virtanen et al., 2011). In particular, Virtanen et al. (2011) presents a carbon footprint of a food portion

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with a focus on the so-called ‘‘finish food’’ sector and the evaluation of the distribution of the climate change impact of the food chain for meat, dairy, catering, grain and other products. Gupta and Palsule-Desai (2011) invite the scientific community to develop integrative and holistic models that can treat the complex trade-offs between operational and sustainable decisions. They affirm that the new challenge is to develop effective models, methods and tools able to treat the non-linear interactions between operational and sustainable decisions. 2.5. Food packaging Food products require a primary package characterized by barrier properties to oxygen and water vapor, in order to limit the phenomena of oxidation and water activity, which would generate a rapid decay of the shelf life and triggering of phenomena of bacteria growth significantly affecting the food safety. The primary packaging represents a fundamental asset and its functional properties are integrated into the system of secondary and tertiary packaging solutions. The frontier of current research in primary packaging development is now oriented towards new types of environmentally friendly solutions (e.g. biodegradable packaging in various acceptations), active packaging (e.g. controlled release of molecules and traditional modified atmosphere packaging – MAP) and functional packaging (e.g. packaging used for cooking in the microwave ready-to-cook products) (Siracusa et al., 2008; Bottani et al., 2011; Mahalik and Nambiar, 2010). Safety in packaging design for food products generally refers both to the preservation of a high quality level and to the prevention of damage to package itself and its content during handling, transportation and other logistic processes. The significance and criticality of the logistic package system design, including primary, secondary and tertiary package solutions, has been recently demonstrated (Azzi et al., in press; Panczel, 2008). 2.6. Technologies and tools for food supply chain Nowadays, excluding manufacturing technologies, which are not the object of this paper, FSC technologies mainly refer to traceability issues with a special focus on high perishable food products subject to rapid deterioration. An effective food traceability system is important tool not only to manage food quality and safety risks, but also to promote the development of effective FSC management. There are two main categories of traceability technologies and devices: identification tags (i.e. barcode, label, RFID tag) which address a product or a general item with a specific code and data loggers (sometimes called ‘‘black boxes’’), whose aim is to trace and record the environmental conditions and profiles experienced by a product throughout SC processes. The development and implementation of such traceability systems for FSC is an effective way to preserve specific features of food products, especially perishable and fresh products, in agreement with safety and quality standards and regulations, and customer satisfaction. In this perspective, it could be useful to monitor all environmental parameters, which could have an impact over quality of products. The food chain monitoring, through proper black box devices, enables to reproduce and simulate ex-post real environmental conditions experienced by products and packaging during logistic processes, e.g. purchasing, manufacturing, handling, warehousing (storage and retrieval), transportation, etc., in order to assess their impacts on food quality and safety. Basically, food deterioration depends on intrinsic and extrinsic factors as storage temperature, concentration of oxygen, relative humidity, solar radiation, acidity, microbial growth, endogenous enzyme activities, etc. (Alasalvar et al., 2001; Howard et al., 1994; Riva et al., 1999; Zhang et al., 2009).

In order to enquire the potential deterioration of food items during the transportation activities, Manzini et al. (2011b) and Bortolini et al. (2011) present a monitoring process and a simulation tool for supporting the evaluation of the stresses affecting products in a specific SC system. Section 5 presents a case study on a monitoring activity and the development and application of an original closed-loop control system. Several literature studies focus on the influence that oneparameter stress (such as temperature, humidity, vibrations) have on products (Xiang and Eschke, 2004; Chonhenchob et al., 2012; Raghav and Gupta, 2003; Mahajerin and Burgess, 2010), and even consider the impact of transportation on foodstuffs (Jarimopas et al., 2008; Chan and Chung-Kee, 2009; Saha et al., 2011). Literature also presents many papers on RFID technologies with several applications in food industry. Wang et al. (2009) and Sarac et al. (2010) analyze traceability problems and issues in order to guarantee food safety within the processing and handling activities in a SC with the aim to manage the additional costs due to the introduction of ICT devices into a competitive advantage. Jones (2006) evaluates the opportunity to apply RFID technology to keep trace of the history of products, while Abad et al. (2009) provide an application of real time traceability of cold chain. Regattieri et al. (2007) introduce a general framework for the implementation of a traceability system in agreement with an evaluation of the logistics impacts and costs. They focused on an application to the Parmigiano Reggiano cheese. A recent review on RFID technologies and applications is presented by Zhu et al. (2012). They present a brief discussion on food and restaurant industry. 2.6.1. RFID in FSC RFID technologies are expensive, require a deep and integrated informative system, and their implementation is a tough challenge for SMEs, which represent 99% of market share in European food industry. Consequently, a synchronous traceability system applied to the whole FSC ‘‘from farm to fork’’ still remains a conceptual framework and an ambitious target for many companies, especially in presence of significantly variable data of product demand in terms of geographical location. The portfolio of consumers/customers can continuously change. For example, the number of customers/consumers can be a few thousands: how is possible to monitor the status of quality and safety of the products at the generic consumer’s location adopting RFID technologies and significantly expensive infrastructures? An interesting discussion of a collaborative environment system based on a multi-agent (MAS) modeling and RFID infrastructure is presented by Reidy et al. (2012), but it is very expensive and there are not yet significant and effective applications. Only a few of very big enterprises have the access to similar investments. This is the reason this paper, supported by the case study, is promoting an ex-post control system of a SC performance by the development and implementation of a closed-loop control system based on a monitoring activity followed by simulation in different what-if operating scenarios (see the case study illustrated below). This is a proactive approach to control integrated FSC systems and an effective alternative to a synchronous, very expensive, and not flexible approach. 2.6.2. Expert system for integrated FSC The integration of the previously mentioned technologies, models and patterns, dealing with the direct-reverse sustainable logistic network, the efficient management of DCs, the monitoring and analysis of FSC, the assessment of food quality and safety, need to be implemented through an integrated expert system as a family of integrated supporting decisions tools (DSSs). They have to collect and store real data about material flows, customers’ demand,

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shipping and transportation activities, food product features in order to provide suitable design and management solutions to address quality, sustainability, efficiency and safety. Literature faces this topic presenting several contributions dealing with integrated informative system solutions and conceptual frameworks (Ali and Bahnasawy, 2011; Van der Vorst et al., 2009; Seebauer, 2011; Lao et al., 2011). However, present tools and information systems concentrate on individual aspects rather than on the entire chain and do not take into account multiple goals, e.g. safety, quality, sustainability and efficiency of the FSC. The literature analysis conducted in this section demonstrates that issues related to FSC are several and significantly interrelated. Literature does not yet present an organic discussion on FSC including all problems and issues, integrated approaches and models, effective supporting decisions tools, conceptual and general frameworks, etc. This is the reason the authors propose a new conceptual framework for FSC assessment and a case study as an exemplifying basis for a closed-loop management and control of the SC of the future in agri-food sector. 3. Integrated FSC. A focus on the integration of quality, safety, sustainability and efficiency issues The final goal of an integrated FSC system is the control of the optimal and interdependent levels of quality (1), safety (2), environmental sustainability (3), and efficiency (4) of the food products (a), food processes (b) and FSC system (c). The complexity of the logistic processes of sourcing/fulfilment, manufacturing and transformation/processing, distribution and consumption of food makes the generic FSC unique and quite different from any other SC. Such characteristic is the result of the previously mentioned macro objectives:

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 Quality: The level of quality and diversity of the raw material is variable and subject to stochastic and contingency rules. The definition of rules, standards and regulations does not fit the uniqueness and singularity of food products, significantly different by region of origin and highly influenced by climate changes, seasonality as well as pollution. The most used definition of the quality of an entity (e.g. product, process) is the measure of the expressed and unexpressed (i.e. not yet explained) expectations of the user/consumer. Consequently, it is necessary to control the level of quality of a food product throughout the FSC from the field to the place of consumption. By a practical point of view, it is not possible, especially in presence of a large and variable portfolio of suppliers and customers located all over the world. This is certainly a new challenge for future research in food sector.  Safety: It evokes the implications of health sector, stringent rules and regulations for the product-packaging system, but also safety of the industry and the communities of people. Several factors are intrinsically capable of damaging or even if marginally affect a food product (e.g. pollution, climate conditions, etc.). The knowledge of these factors and the correlation with the safety parameters can prevent the occurrence of damage to the community and the environment. Logistics and operations, including packaging and other engineering and non-engineering disciplines (e.g. microbiology, food science, medicine, etc.) can play a proactive role in the control of safety.  Sustainability: In 2011 the European Environment Agency declared that the food and drink sector contributes to some 23% of global resource use, 18% of greenhouse gas emissions and 31% of acidifying emissions (EEA, 2010). Sustainability in FSC is increasingly a ‘‘must’’ and one of the most important challenges is to ensure sustainable development and growth

Fig. 1. FSC environmental impacts (inspired to EEA, 2010).

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The others main macro-operations/activities are: consolidation (ii), manufacturing & processing (iii) and packaging & distribution (iv). All issues and decisions are grouped in two main groups identifying the competences necessary to best support the activities of planning, design, management and control of a food supply system. These groups of expertise are: a. Engineering group. In particular, the competences belong to logistics and operations management with a focus on engineering design, planning and quality/safety assessment. b. Agriculture group. In particular, the competences belong to food science, microbiology and chemistry.

Fig. 2. Goals of an integrated food supply chain management and control.

starting from the sharing of information among all the actors of the sector. Fig. 1 presents the most important environmental impacts generated within a generic FSC. Resource inputs (e.g. land, water, energy, fossil fuel) generate outputs (e.g. waste, emission to air, soil loss) as impacts for the environment at different level of the chain (e.g. procurement, food processing, handling, consumption, etc.).  Logistics efficiency is synonymous with productivity achieved through cost control, resource control and waste reduction throughout the whole SC. Quality, safety, sustainability and efficiency of a FSC implicitly include the quality, safety, sustainability and efficiency of food products. For example, it is very important to measure the level of quality and safety of a foodstuff at the consumer location to affirm that the whole supply system operates at high levels of customers’ (i.e. consumers’) quality and safety. However, quality and safety significantly affect all the stakeholders, including the environment and the society (i.e. the community of people), directly and indirectly operating within the system from ‘‘farm/field to fork’’. Similarly, efficiency and sustainability measures and performance have to be continuously collected during the journey of a food product from harvesting to consumption in order to quantify all cost contributions, including environmental impacts and social effects. Fig. 2 shows the levels of quality, safety, sustainability and efficiency of a system as the results of the decisions on manufacturing and processing, direct and indirect logistics (including packaging). This is the integrated focus supported by the proposed conceptual framework for an FSC assessment as illustrated in detail in next section.

4. A new conceptual framework for FSC assessment Fig. 3 presents an original conceptual framework for FSC in agreement with a multi-discipline point of view. This is the result of the integration of multiple decisions affecting the performance of the system, made of many and different stakeholders. Quality, safety, sustainability and efficiency summarize the main KPIs and drivers for the integration of the food chain ‘‘from farm to fork’’. The large number of problems, issues and decisions are reported in figure and grouped in agreement with macro operations and activities: from ‘‘Products and raw materials’’ (i) collection and harvesting to ‘‘consumption and end-life cycle’’ (v), which directly involves the consumer eventually located far away from the production site.

The huge number of partners involved in a FSC, the complex data flow, the coexistence of different majors and points of view to address criticalities, and the variability in food products mainly affect the analysis, the evaluation and the assessment of the whole system. The integration of several research topics, majors, and expertise on chemistry, food science, engineering and economics allows a joint and common approach to address FSC issues through the adoption of multi-objective and multi-purpose models and techniques. This scheme shows the principal decisions and issues generated by an integrated approach to modeling food chains. A few examples: selection of agriculture products and farming products to be processed and supplied in accordance with weather conditions, climate seasonality, and demand forecasts; selection of geographic site or region suitable for harvesting and farming based on the environmental impacts, the location of manufacturing and distribution facilities and the related logistics and transportation costs; definition of KPIs to jointly assess and compare logistic processes and their impacts on the chemical-organoleptic characteristics of food products. This new approach to FSC assessment supports and promotes a new model of sustainable ‘‘eco-farm’’ concerning with harvesting and raw material purchasing, and a new model of ‘‘eco-factory’’ responsible for the sustainable processing and product manufacturing, for the proactive maintenance of plants, for the machines monitoring, for the efficient industrial throughput. This new ecofactory approach is based on the following activities:  manufacturing optimization to comply efficiency, quality and safety of food products and people;  development of lean manufacturing sustainable solution in food industry;  on-board machine monitoring for chemical-organoleptic characteristics of food products;  maintenance planning of technologies and plants depending on the quality thresholds of food products; etc. Finally, the proposed framework recognizes the importance of developing innovative models of ‘‘eco-logistics’’ in FSC. The aim is to plan the purchasing and consolidation of raw materials by the strategic and operative prospective, the distribution towards final consumers/customers, the reverse flow of packages due to post life-treatments in agreement with shelf-life constraints, costs and environmental impacts. Finally, the proposed framework aims to support the following additional targets: (1) the optimization of overall logistic network (forward–reverse) taking into account economical and environmental aspects; (2) the design of distribution centers specially devoted to food products and food chain; (3) the monitoring and control of shipping and storing conditions experienced by food products during their journey towards consumers; (4) the analysis of degradation phenomena occurred to food products and packaging throughout the logistic system.

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Fig. 3. Food supply chain conceptual framework.

4.1. Future challenges in FSC In agreement with the previously introduced conceptual framework, the major challenges generated by the proposed integrated FSC perspective and objects of interest for final consumers and stakeholders, vendors, logistic providers and operators, PDO products (e.g. Made in Italy products) and producers, packaging manufacturers, academic and private/public research, environment and society, innovation and progress, are:  definition of a panel of effective KPIs to characterize simultaneously products, process efficiency, sustainability and safety, and to monitor and control integrated FSCs;  design, development and testing of innovative systems and devices for the diagnostic and close-loop control of a FSC, in terms of quality, safety, sustainability, efficiency (see the case study illustrated in Section 5),  design of innovative technologies for products and process traceability;  development of innovative technologies, materials and solutions in primary (e.g. cold plasma, bio-material, biodegradable material), secondary and tertiary packaging, suitable for logis-

 



 



tics (material handling, warehousing in storage systems and shipment), development of models and techniques for risk assessment in FSC; design and development of ICT solutions and expert systems (and DSSs) to support decisions on strategic planning of land use, of facilities sites and operations management within a FSC; definition and dissemination of useful guidelines, standards, procedures, models and results for stakeholders, institutions, enterprises and researchers, in order to fulfil needs in FSC and to revise general rules; promotion of coordination and cooperation approaches in handling FSC issues; promotion of consumer-focused culture in order to manage risk, to comply safety and quality needs and environmental requirements (green demand, environmental care products), promotion of eco-friendly culture for environmental sustainability, progress and society needs.

As previously discussed in Section 2, literature presents several conceptual frameworks (‘‘holonic architectures’’), informative system architecture and operational models (e.g. ‘‘multi-agent

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systems’’) concerning with logistics and SCM (e.g. based on RFID technologies), but no economical solutions suitable for Small and Medium Enterprises (SMEs). A few international enterprises involved in grocery and retailing have implemented dynamic informative architecture upon pilot projects. Unfortunately these solutions might not be applied whether costumers, manufacturing and distribution facilities are numerous and worldwide spread (as in case of import/export enterprises), especially within not owned supply chains. 5. A case study This case study presents the development and application of a proactive ex-post and closed-loop control system as the first step to a synchronous control of a FSC. This is an effective way to measure and control the variability of the demand of perishable products in terms of variants and typologies of food (at different level of quality at the production site), requested volumes and quantities, geographical locations for the points of demand and consumption, available primary, secondary and tertiary packaging solutions, shipping container solutions, etc. The aim of this case study is to define the first basis for the control of the level of quality (1), safety (2), sustainability (3) and efficiency (3) of a food chain with a special focus on the distribution system. Fig. 4 presents the logic scheme of the adopted closed-loop control system. Input of this control system is the existing FSC configuration (named AS-IS). The proposed control system is made of two main blocks: the monitoring block and the simulator block. They correspond to two distinct decisional steps. The monitoring of a food chain is the basic step of the proposed control and assessment process. The aim is to measure the physical and environmental conditions, which could affect the level of quality, safety, sustainability and efficiency of the FSC. This task is the result of the adoption of commercial and not commercial technologies for monitoring the physical and environmental stresses (e.g. temperature, humidity and vibrations) affecting packages during the shipment. A typical shipment starts from the production site to the local wholesaler headquarter frequently located far away

from the production site and frequently from the consumption location. Piazzi et al. (2011) and Bortolini et al. (2011) present some applications of an original black-box and commercial data-loggers for the execution of the monitoring process. The aim is the collection of physical and environmental stresses generated during a logistic operation, e.g. the shipment to the final consumer. In particular, Piazzi et al. (2011) present a problem-oriented blackbox. We call this ‘‘problem-oriented’’ because it has been developed and applied specifically for food shipment monitoring in presence of multiple stresses measurement. Another basic technological block of this closed-loop control system is the simulation system (see the ‘‘simulation’’ task in Fig. 4). It is a climate room simulator able to simulate the monitored physical and environmental stresses, e.g. time-dependent temperature variability, in order to measure directly the effects due to international and intercontinental shipments. An illustration of the adopted simulation system is discussed by Bortolini et al. (2011). The system illustrated in Fig. 4 is based on two different loops: 1. First loop: (Loop 1 in Fig. 4). It deals with the laboratory multiscenario simulation analysis. The simulation activity gives the decision-maker the opportunity to measure the effects of different logistics decisions in a what-if environment. The so-called ‘‘sensed values’’, output of the simulation run, are compared with the ‘‘expected (target) values’’. As a result, the feedback is good (‘‘Feedback OK’’ in Fig. 4) when the expected values, or more performing KPIs than the expected one, are generated; otherwise (‘‘Feedback NO OK’’ in Fig. 4) system modifications and adjustments are expected and can be applied in a new set of simulation runs. 2. Second loop: (Loop 2 in Fig. 4). It deals with the continuous improvement of the performance of the whole logistic system. The monitoring and simulation tasks are the bases of the proposed control and assessment process of a FSC. This closed-loop system has been applied to the SC of an Italian company which distributes edible oils worldwide, e.g. far east (Taiwan, China, Japan, etc.), north and south of America (USA, Canada, Brazil), etc.

Fig. 4. Closed-loop control system. Case study.

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More than any other countries, Italy represents the proper context for the development of a modern efficacy, sustainable and integrated FSC, due to the complexity, the importance and the impact that the food industry and the Italian food specialties play in the global food exports. The Italian food system contributes to the positive image of the well-known ‘‘Made in Italy’’ and represents one of the pillars of the national economy with a turnover in 2010 of 124 billion euro, whose about 21 billion coming from exports. At least 238 food products of ‘‘Made in Italy’’ are recognized as PDO products (including 40 extra virgin different types of olive oil), in addition to 519 different types of wines (Squarcia, 2011). Italy counts about one third of the European biological companies and covers more than a quarter of the organic crops production of the EU (Romito and Marras, 2011). 5.1. Problem identification Fig. 6. Oil drawing, example (Ref. aluminum enclosure).

The most suitable packaging and shipping solution for international shipping is the intermodal freight container. The adopted tertiary package is the palletized unit load made of multiple layers of secondary packages, each made of 6 or 12 bottles of oils (the primary packages). Fig. 5 shows the trend of the monitored temperature in an international shipment from Bologna (Italy) to Kaohsiung (Taiwan). Products contained in the container are Italian wines and oils for food (extra virgin olive oil and grape seed oils). This graph shows two different trends related to the monitored temperature closed to the door of the container (‘‘Door’’ in Fig. 5) and the temperature level monitored in a baricentric location (‘‘Middle’’ in Fig. 5). The maximum level of temperature was about 56 °C (‘‘middle’’ temperature). This is the level corresponding to the container of products waiting at the seaport in Singapore. This is a very critical time window usually not directly controlled by the logistic distributor. Consequently, this temperature is significantly affected by the climate conditions and particularly by solar radiation exposure. Extra virgin olive oil bottles, rice oil bottles and grape seed oil bottles took part to this journey from Italy to Taiwan. Then, a few samples of the same production lots were subjected to the simulation analyses illustrated in next section.

Fig. 6 shows what happened at the arrival of the container in Kaohsiung during the monitored shipment: many bottles of oils leaked out from the enclosure due to the thermal dilatation and viscosity of the oil. Fig. 6 illustrates an aluminum enclosure of a glass bottle but this damage happened in presence of different packages and enclosures. In these scenarios, the customer usually rejects the container because it does not respect the standard of safety and quality. This generates an extra cost of logistics eventually including the disposal cost contribution. 5.2. Simulation analyses and new packaging solutions In order to identify new logistic solutions able to reduce the previously illustrated problem, which generates significant costs, inefficiencies and environmental effects (due to the return of containers and the disposal of products), we have introduced and tested new enclosures by the use of the laboratory of simulation previously illustrated. This climate room enables the measurement of packages performance under different temperature conditions and profiles.

Fig. 5. Temperature profile in Celsius degrees monitored from Italy to Taiwan.

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Different simulation runs have been conducted in order to identify the best combination of packaging enclosures applied to the most critical bottle (the 1,000 ml glass bottle). Two new packaging plastic enclosures, named ‘‘NEW’’ and ‘‘NEW2’’, have been tested comparing the results obtained by the adoption of the ‘‘old’’ plastic enclosure (the first illustrated in Fig. 7). NEW and NEW2 differ for the absence (NEW) and presence (NEW2) of a sleever on the plastic cap of the bottle. We conducted two different analyses based on simulation by the adoption of the closed-loop system illustrated in Fig. 4. 5.2.1. Shipment simulation The first analysis compares the performance of the three typologies of enclosures by the simulation in the climate room of the

Fig. 7. ‘‘Old’’AS-IS configuration vs ‘‘NEW’’ and ‘‘NEW2’’ enclosures.

temperature profile monitored during the ‘‘monitoring task’’ applied to the selected shipment from Italy to Taiwan. The ex-post simulation of this international journey demonstrates that the new packaging solutions (‘‘NEW’’ and ‘‘NEW2’’) best perform than the ‘‘old’’ one, and the oil does not leak out from the new enclosures. As a result NEW and NEW2 guarantee the reliability of the packaging solution during a shipment whose temperature exposure profile is not more critical than the profile monitored (shipment Italy-Taiwan). What happen to the packages NEW and NEW2 when they are stressed at different level of temperature eventually greater than the levels monitored in this specific journey? To find an effective answer to this question we conducted a second analysis based on the use of the proposed closed-loop control system. 5.2.2. Accelerated life testing analysis The second analysis deals with the application of the closedloop simulation system to directly compare the performance of ‘‘NEW’’ and ‘‘NEW2’’. To this purpose, an accelerating life test (ALT) analysis has been conducted (Manzini et al., 2010). ALT involves the acceleration of failures with the single purpose of quantifying the life characteristics of the product at normal, i.e. nominal, use conditions. Which are the use conditions of shipment of perishable products? Which are the use conditions for the products object of this case study? We know what happen in a specific shipment or in a set of monitored journeys. We conduct ALT analysis to predict the behavior and reliability information of the proposed new packaging solutions in different realistic and not realistic operating scenarios. To this purpose different simulation runs at different levels of constant temperature have been executed. The time to failure (ttf) values, as the time the oil leaks out from the bottle, have been collected.

Fig. 8. Life vs stress analysis. Vinacciolo oil.

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Several reliability analyses can be conducted. One of the most useful is the ‘‘life time’’ prediction of the bottle adopting different enclosures. An illustration of the ALT theory and applications is presented by Manzini et al. (2010, 2011b). Fig. 8 presents the so-called Life Stress analysis for a special typology of critical oil, characterized by low values of viscosity. This is the grape seed edible oil. The analysis plots the expected life of a bottle (see Fig. 8). This is the so-called time to failure (on the y-axis in [minutes]), i.e. the time the failure occurs given a constant stress of temperature. The failure event corresponds to the oil leaking from the enclosure when subject to different stress levels (on the x-axis in Kelvin temperature degree). This analysis is the results of the multiple application of the simulator system operating at different temperatures and in presence of samples of multiple bottles of the three types of packages. Given a level of temperature (e.g. 60 °C) and a sample of bottles (e.g. package NEW) the Weibull density function as the statistical and parametric distribution best fitting the collected time to failures is plotted. These time values also include censored data. In Fig. 8, the line named ‘‘package NEW’’ is the line fitting the mean expected value of ttf for different stress levels of temperature and the NEW enclosure. Similarly, the continuous line, named package NEW2, refers to the package NEW2. NEW2 performs better than NEW, even if the difference between the expected failure times for the two packages reduce for very high levels of temperature. We decided to not further discuss ALT theory and the obtained results because this is not the object of this paper. An in-depth description of a similar ALT analysis has been presented by Manzini et al. (2011b). Similar analyses can be conducted in a what-if scenarios in agreement or not in agreement with a set of monitored physical and environmental conditions, eventually including other SC processes, e.g. manufacturing, warehousing and material handling, etc.

6. Conclusions and further research Logistics plays an increasingly important role in FSC, but this awareness must grow more and more to be shared between different actors in the chain. This is demonstrated by the expectations of the European-oriented research, as early as the 7th Framework Programme, but especially the new Framework Programme 2014–2020, Horizon 2020. In Horizon 2020 food safety, transportation, sustainability and SC are issues of strategic interest. In particular, the consortium FoodBEST (www.foodbest.eu) has been delegated to participate to the definition of the contents of Horizon 2020 on the theme food. This consortium is working on the kicfood approved by the European Institute of technology (EIT) at the end of 2011 and included into the new European Programme 2014–2020. The name of this kic is ‘‘food4future’’ (‘‘sustainable food supply chain, from farm to fork’’) explicitly focused on SC and sustainability. Nowadays, the knowledge of the status of quality of most critical products often stops at the gates of the producer without any investigation on the status of quality at the consumer’s location. This location can be variable and placed in a different countries and continents due to the pressure of the markets globalization. Food scientists know some effects on foodstuffs as generated by the uncontrolled exposition to light, heat, variability of temperature and pressure, vibrations and mechanical shock. However, this knowledge is not complete and rarely has been correlated to the logistics decisions, e.g. transport and packaging. In addition, the extreme and unexpected climatic conditions affecting the SC can severely compromise the level of quality of the product during the life cycle and the safety for the final consumer.

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One of the most important challenge for future research in FSC integration and food logistics research is the measurement of correlations between logistics operations and decisions (e.g. shipment typologies, transportation modes, packaging solutions, environmental and climatic conditions), multi stress monitoring and evaluation, quality and safety effects of food products at the point of consumption. There are evident lacks about the contemporary influence of the environmental factors previously mentioned and there are few works presenting experimental devices able to provide a simultaneous control of multiple stresses, e.g. temperature, humidity, vibrations, ambient pressure and light exposure. Some efforts have been made in the pharmaceutical and in the biochemical sectors (Foster et al., 2006), but never taking into account the possibility of an integrated approach on testing food products. The proposed conceptual framework demonstrates that the integration of competences, problems, issues and decisions is the most important future challenge in FSC. This integration involves the processes of design, planning, management and control of the logistics system. Many food chains and enterprises are interested in this challenge. In particular, several companies are interested in a complete traceability of products, processes and systems. To this purpose IC technology suggests the development and application of expensive RFID-based solutions, which are certainly effective for product traceability and theoretically useful to synchronously control a SC system. However, 99% of food enterprises in Europe are SMEs and very few multinational companies can afford such investments, unable in practice to measure and control simultaneously the levels of quality, safety, sustainability and efficiency on the table of the consumer, especially in markets continuously evolving. Coompanies are waiting for effective and not too expensive solutions for SC systems, eventually based on remotely, and not synchronous, flexible and closed-loop control devices. The proposed closed-loop control system based on simulation and illustrated in Section 5 is a first exemplifying step towards a synchronous control of the whole food supply system, even if the application is mainly focused on packaging issues. No direct measures of quality and safety have been yet included. This case study demonstrates the importance of a new approach to FSC in order to control the temperature profile. Similarly, other control parameters can be included and simultaneously controlled, e.g. vibrations, light exposure, etc. The proposed original conceptual framework for FSC assessment and the approach exemplified by the case study, is the first basis for an effective and direct control of safety, quality, sustainability and efficiency, which remain the challenge of the future research. There is still a lot of work for public and private research institutions. Acknowledgements The authors would like to thank the anonymous referees for their constructive input and comments, which served to improve the manuscript. References Abad, E., Palacio, F., Nuin, M., González de Zárate, A., Juarros, A., Gómez, J.M., Marco, S., 2009. RFID smart tag for traceability and cold chain monitoring of foods: demonstration in an intercontinental fresh fish logistic chain. J. Food Eng. 93 (4), 394–399. Accorsi, R., Bortolini, M., Ferrari, E., Manzini, R., Mora, C., Pareschi, A., Regattieri, A., 2011. Economical and environmental assessment of multi-use package within food catering chain: an Italian case study. Proceedings of the First International Workshop on Food Supply Chain – WFSC. Bertinoro (FC) – Orvieto (TR), Italy. Ahumada, O., Villalobos, J.R., 2009. Application of planning models in the agri-food supply chain: a review. Eur. J. Oper. Res. 196 (1), 1–20. Alasalvar, C., Grigor, J., Zhang, D., Quantick, P., Shahidi, P., 2001. Comparison of volatiles, phenolics, sugars, antioxidant vitamins, and sensory quality of different colored carrot varieties. J. Agric. Food Chem. 49, 1410–1416.

262

R. Manzini, R. Accorsi / Journal of Food Engineering 115 (2013) 251–263

Ali, S.A., Bahnasawy, A.H., 2011. Decision support system for technical management of food processing industries Source. Proceedings – 2011 International Conference on Internet Computing and Information Services. ICICIS, 20–24. Alumur, Sibel, Kara, Bahar, Y., 2008. Network hub location problems: the state of the art. Eur. J. Operational Res. 190 (1), 1–21. Apaiah, R.K., Hendrix, E.M.T., Meerdink, G., Linnemann, R., 2005. Qualitative methodology for efficient food chain design. Trends Food Sci. Technol. 16, 204–214. Apaiah, R.K., Linnemann, A.R., van der Kooi, H.J., 2006. Energy analysis: a tool to study the sustainability of food supply chain. Food Res. Int. 39, 1–11. Azzi, A., Battini, D., Persona, A., Sgarbossa, F., in press. Packaging design: general framework and research agenda. Packaging Technology and Science. doi: http:// dx.doi.org/10.1002/pts.993. Barchi, G.L., Berardinelli, A., Guarnieri, A., Ragni, L., Totaro Fila, C., 2002. Damage to loquats by vibration-simulating intra-state transport. Biosyst. Eng. 82, 305–312. Bartholdi, J., Hackman, S.T., 2011. Warehouse & distribution science. (accessed August 2011). Beamon, B.M., 1998. Supply chain design and analysis. Int. J. Prod. Econ. 55, 281– 294. Beamon, B.M., 1999. Designing the green supply chain. Logistics Information Manage. 12 (4), 332–342. Berardinelli, A., Donati, V., Giunchi, A., Guarnieri, A., Ragni, L., 2003a. Effects of sinusoidal vibrations on quality indices of shell eggs. Biosyst. Eng. 86, 347–353. Berardinelli, A., Donati, V., Giunchi, A., Guarnieri, A., Ragni, L., 2003b. Effects of transport vibrations on quality indices of shell eggs. Biosyst. Eng. 86, 495–502. Berardinelli, A., Donati, V., Giunchi, A., Guarnieri, A., Ragni, L., 2006. Mechanical behavior and damage of pink lady apples. Appl. Eng. Agric. 22, 707–712. Bortolini, M., Gamberi, M., Accorsi, R., Manzini, R., Mora, C., 2011. Food products thermal stress: a temperature controlled climate room for simulations and tests of the shipping conditions. Proceedings of the XVI Summer School ‘‘Francesco Turco’’ – Industrial Mechanical Plants. XVI Summer School ‘‘Francesco Turco’’ – Industrial Mechanical Plants, 14–16 September 2011, Abano Terme (Padova, Italy), pp. 1–6. ISBN: 9788890631924. PADOVA: Università di Padova (Italy). Bosona, T.G., Gebresenbet, G., 2011. Cluster building and logistics network integration of local food supply chain source. Biosyst. Eng. 108 (4), 293–302. Bottani, E., Montanari, R., Vignali, G., Guerra, L., 2011. A survey on packaging materials and technologies for commercial food products. Int. J. Food Eng. 7 (1), 2011. Boulton, R.B., Singleton, V.L., Bisson, L.F., Kunkee, R.E., 1996. Principles and Practices of Winemaking. Kluwer, NY. Calligaris, S., Manzocco, L., Kravina, G., Nicoli, M.C., 2007. Shelf-life modeling of bakery products by using oxidation indices. J. Agric. Food Chem. 55, 2004–2009. Carter, C.R., Easton, P.L., 2011. Sustainable supply chain management: evolution and future directions. Int. J. Phys. Distribution Logistics Manage. 141 (1), 46–62. Chaabane, A., Ramudhin, A., Paquet, M., 2012. Design of sustainable supply chains under the emission trading scheme. Int. J. Prod. Econ. 135, 37–49. Chan, H.Y., Chung-Kee, Y.E.H., 2009. Monitoring of the vibration damage for packaging mangos in a corrugated fiberboard box during transportation. 5th International Technical Symposium on Food Processing, Monitoring Technology in Bioprocesses and Food Quality Management, pp. 484–489. Chen, H.-K.H., Che-Fu Chang, M.-S., 2009. Production scheduling and vehicle routing with time windows for perishable food products. Comput. Oper. Res. 36 (7), 2311–2319. Chonhenchob, V., Singh, S.P., Singh, J.J., Stallings, J., Grewal, G., 2012. Measurement and analysis of vehicle vibration for delivering packages in small-sized and medium-sized trucks and automobiles. Packaging Technol. Sci. 25 (1), 31–38. Christopher, M., Holweg, M., 2011. Supply chain 2.0: managing supply chains in the era of turbulence. Int. J. Phys. Distribution Logistics Manage. 41 (1), 63–82. Das, K., Chowdhury, A.H., 2012. Designing a reverse logistics network for optimal collection, recovery and quality-based product-mix planning. Int. J. Prod. Econ. 135, 209–221. De Koster, R., Le-Duc, T., Roodberger, J., 2007. Design and control of warehouse order picking: a literature review. Eur. J. Operational Res. 18, 481–501. Di, Weimin Wang, Jinfeng, Li, Bingjun, Wang, Meijie, 2011. A location-inventory model for perishable agricultural product distribution centers. Source: 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce, AIMSEC 2011 proceedings, pp. 919–922. Dreyer, H.C., Alfnes, E., Strandhagen, J.O., Thomassen, M.K., 2009. Global supply chain control systems: a conceptual framework for the global control centre. Prod. Planning Control 20 (2), 147–157. EEA, 2010. European Environment Agency 2010. The European Environment. State and outlook 2010. Consumption and the environment. Farahai, R.Z., SteadieSeifi, M., Asgari, N., 2010. Multiple criteria facility location problems: a survey. Appl. Math. Modell. 34 (7), 1689–1709. Federalimentare, 2012. . Fisher, M.L., 1997. What is the right supply chain for your product? Harvard Business Rev. 75 (2), 105. Fleischmann, B., Meyr, H., Wagner, M., 2005. Advanced planning. In: Wagner, M. (Ed.), Supply Chain Management and Advanced Planning: Concepts Models, Software and Case Studies. Springer, Berlin, Germany (Chapter 4). Foster, A.M., Ketteringham, L.P., Swain, M.J., Kondjoyan, A., Havet, M., Rouaud, O., Evans, J.A., 2006. Design and development of apparatus to provide repeatable surface temperature–time treatments on inoculated food samples. J. Food Eng. 76 (1), 7–18.

Fox, P.F., McSweeney, P.L.H., Cogan, T.M., Guinee, T.P., 2004. Cheese – Chemistry, Physics and Microbiology. General Aspects, vol. 1. Elsevier, London, UK. Frankel, E.N., 1991. Recent advances in lipid oxidation. J. Sci. Food Agric. 54, 495– 511. Gamberini, R., Gebennini, E., Manzini, R., Ziveri, A., 2010. On the integration of planning and environmental impact assessment for a WEEE transportation network – A case study. Resour. Conserv. Recy. 54, 937–951. Gebennini, E., Gamberini, R., Manzini, R., 2009. An integrated production– distribution model for the dynamic location and allocation problem with safety stock optimization. Int. J. Prod. Econ. 122, 286–304. Goff, H.D., Hill, A.R., 1993. Chemistry and physics. In: Hui, Y.H. (Ed.), Dairy Science and Technology Handbook. Principles and Properties, vol. 1. Vhc, NY, USA. Gopakumar, B.S.S., Wang, S., Koli, S.S., 2008. A simulation based approach for dock allocation in a food distribution center. Source: Proceedings-winter Simulation Conference, Proceedings of the 2008 Winter Simulation Conference, pp. 2750– 2755. Green, D.P., 2010. Sustainable food supply chains. J. Aquat. Food Prod. Tech. 19 (2), 55–56. Gu, J., Goetschalckx, M., McGinnis, L.F., 2007. Research on warehouse operation: a comprehensive review. Eur. J. Oper. Res. 177, 1–21. Gunasekaran, A., Ngai, E.W.T., 2012. The future of operations management: an outlook and analysis. Int. J. Prod. Econ. 135, 687–701. Gupta, S., Palsule-Desai, O.D., 2011. Sustainable supply chain management: review and research opportunities. IIMB Manage. Rev. 23, 234–245. Holweg, M., Disney, S., Holmström, J., Småros, J., 2005. Supply chain collaboration: making sense of the strategy continuum. Eur. Manage. J. 23 (2), 170–181. Howard, L.R., Griffin, L.E., Lee, T., 1994. Steam treatment of minimally processed carrot sticks to control surface discoloration. J. Food Sci. 59, 356–358. Hsu, C.-I., Hung, S.-F., Li, H.-C., 2007. Vehicle routing problem with time-windows for perishable food delivery source. J. Food Eng. 80 (2), 465–475. Jarimopas, B., Rachanukroa, D., Singh, S.P., Sothornvit, R., 2008. Post-harvest damage and performance comparison of sweet tamarind packaging. J. Food Eng. 88 (2), 193–201. Jayaraman, V., Luo, Y., 2007. Creating competitive advantages through new value creation: a reverse logistics perspective. Acad. Manage. Perspect. 21 (2), 56–73. Jones, P., 2006. Networked RFID for use in the food chain, Emerging Technologies and Factory Automation, 2006, ETFA ‘06, pp. 1119–1124. Labuza, T.P., 1982. Shelf-Life Dating of Foods. Food & Nutrition Press, Westport, CT, USA. Lambert, D.M., Cooper, M.C., 2000. Issues in supply chain management. Ind. Mark. Manage. 29, 65–83. Lao, S.I., Choy, K.L., Ho, G.T.S., Tsim, Y.C., Lee, C.K.H., 2011. Real-time inbound decision support system for enhancing the performance of a food warehouse. J. Manuf. Technol. Manage. 22 (8), 1014–1031. Li, K., Ganesan, V.K., Sivakumar, A.I., 2006. Methodologies for synchronised scheduling of assembly and air transportation in a consumer electronics supply chain. Int. J. Logistics Syst. Manage. 2 (1), 52–67. Mahalik, N.P., Nambiar, A.N., 2010. Trends in food packaging and manufacturing systems and technology. Trends Food Sci. Technol. 21 (3), 117–128. Mahajerin, E., Burgess, G., 2010. Investigation of package vibration during the repetitive shock test. WCE 2010 – World Congr. Eng. 2, 1016–1018. Man, C.M.D., Jones, A.A., 1994. Shelf Life Evaluation of Foods. Blackie Academic & Professionals, Glasgow, UK. Manzini, R., 2012a. A top–down approach and a decision support system for the design and management of logistic networks. Transp. Res. E 48 (6), 1185–1204. Manzini, R., 2012b. Warehousing in the global supply chain. Advanced models, tools and applications for storage systems. ISBN: 978-1-4471-2273-9. Manzini, R., Gebennini, E., 2008. Optimization models for the dynamic facility location and allocation problem. Int. J. Prod. Res. 46 (8), 2061–2086. Manzini, R., Bindi, F., 2009. Strategic design and operational management optimization of a multi stage physical distribution system. Transp. Res. E 45, 915–936. Manzini, R., Gamberi, M., Gebennini, E., Regattieri, A., 2008. An integrated approach to the design and management of a supply chain. Int. J. Adv. Manuf. Technol. 37, 625–640. Manzini, R., Regattieri A., Pham, H., Ferrari, E., 2010. Maintenance for industrial systems. Springer London Ltd., London XVIII, 479, p. 507 illus., Hardcover. ISBN: 978-1-84882-574-1. Manzini, R., Bortolini, M., Gamberi, M., Montecchi, M., 2011a. A supporting decision tool for the integrated planning of a logistic network. In: Sanda Renko (Ed.), Supply Chain Management – New Perspectives, ISBN: 978-953-307-633-1, InTech. Manzini, R., Accorsi, R., Bortolini, M., Gamberi, M., Magnani, F., Marinelli, G., 2011b. Accelerating life testing for food packaging. A case study of Italian oil-for-food distribution. Proceedings of the First International Workshop on Food Supply Chain, June 26 – July 1, Bertinoro (FC) – Orvieto (TN), Italy. ISBN: 9788890650000. Manzini, R., Bortolini, M., Ferrari, E., Piergallini, A., 2011c. A supporting decision tool for reverse logistics. Proceeding of the 21st International Conference on Production Research ICPR 21, July–August, Stuttgart, Germany. Marucheck, A., Greis, N., Mena, C., Cai, L., 2011. Product safety and security in the global supply chain: issues, challenges and research opportunities. J. Oper. Manage. 29, 707–720. Melo, M.T., Nickel, S., Saldanha-da-Gama, F., 2009. Facility location and supply chain management – a review. Eur. J. Operational Res. 96, 401–412.

R. Manzini, R. Accorsi / Journal of Food Engineering 115 (2013) 251–263 Min, H., Ko, H., Ko, C., 2006. A genetic algorithm approach to developing the multiechelon reverse logistics network for product returns. Omega-Int. J. Manage. Sci. 34 (1), 56–69. Nagy, G., Salhi, S., 2007. Location–routing: issues, models and methods. Eur. J. Oper. Res. 177, 649–672. Osvald, A., Stirn, L.Z., 2008. A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food Source. J. Food Eng. 85 (2), 285–295. Osvald, A., Stirn, L.Z., 2008. A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food source. J. Food Eng. 85 (2), 285–295. Piazzi, P., Adami, S., Bortolini, M., Gamberi, M., Accorsi, R., Manzini, R., 2011. Design, development and test of a vibration monitoring embedded system. Proceedings of the First International Workshop on Food Supply Chain. First International Workshop on Food Supply Chain, June 26 – July 1 2011, Bertinoro (FC) – Orvieto (TN), Italy. ISBN: 9788890650000. Prajogo, P., Olhager, J., 2012. Supply chain integration and performance. The effects of long-term relationships, information technology and sharing, and logistics integration. Int. J. Prod. Econ. 135, 514–522. Raghav, P.K., Gupta, A.K., 2003. Simulated transportation of individually shrink wrapped kinnow fruits. J. Food Sci. Technol. 40 (4), 389–397. Regattieri, A., Gamberi, M., Manzini, R., 2007. Traceability of food products: general framework and experimental evidence. J. Food Eng. 81, 347–356. Reidy, P.J., Gunasekaran, A., Spalanzani, A., 2012. Buttom–up approach based on a multi-agent system for orde fulfillment in a collaborative warehousing environment. Seventeenth International Working Seminar on Production Economics. Seventeenth International Working Seminar on Production Economics, vol. 3, INNSBRUCK, Austria, pp. 1–11. Riva, M., Piergiovanni, L., Galli, A., 1999. Valutazione della shelf-life di vegetali freschi confezionati preparati per il consumo. Proceedings of IV Italian Congress of Food Science and Technology (CISETA), pp. 207–222. Rogers, D., Tibben-Lembke, R., 1999. Going backwards: reverse logistics trends and practices. Romito, G., Marras, F., 2011. BIOReport 2011. L’agricoltura biologica in Italia. MIPAA F COSVIR II. Roy, P., Nei, D., Orikasa, T., Xu, Q., Okadome, H., Nakamura, N., Shiina, T., 2009. A review of life cycle assessment (LCA) on some food products. J. Food Eng. 90, 1– 10. Saha, K., Singh, S.P., Singh, J., 2011. Sensory evaluation of fresh cut mangos packaged in rigid containers subjected to mechanical abuse by transport vibration. J. Appl. Packaging Res. 5 (3), 181–195. Sarac, A., Absi, N., Dauzere-Peres, S., 2010. A literature review on the impact of RFID technologies on supply chain management. Int. J. Prod. Econ. 128, 77–95. Seebauer, M., 2011. Expert system for optimization of food consumption in intelligent home source. 9th IEEE International Symposium on Applied Machine Intelligence and Informatics, SAMI 2011 – Proceedings, pp. 255–258.

263

Sing, A., Singh, Y., 1992. Effects of vibration during transportation on the quality of tomatoes. Agric. Mechanization Asia, Africa and Latin America 23, 70–72. Sing, S.P., Xu, M., 1993. Bruising in apples as a function of truck vibration and packaging. Appl. Eng. Agric. 9, 455–460. Singh, R.K., Singh, N., 2005. Quality of packaged foods. In: Han, J.H. (Ed.), Innovations in Food Packaging. Elsevier Academic Press. Singh, P.J., Power, D., 2009. The nature and effectiveness of collaboration between firms, their customers and suppliers: a supply chain perspective. Supply Chain Manage. Int. J. 14 (3), 189–200. Siracusa, V., Rocculi, P., Romani, S., Della Rosa, M., 2008. Biodegradable polymers for food packaging: a review. Trends Food Sci. Technol. 19 (12), 634–643. Squarcia A., 2011. Numero dei vini a D.O.C.G. – D.O.C. – I.G.T. all’11 Ottobre 2011. Quadro riepilogativo. Ministero delle Politiche Agricole Alimentari e Forestali. Virtanen, Y., Kurppa, S., Saarinen, M., Katajajuuri, J.M., Usva, K., Mäenpää, I., Makelä, J., Grönroos, J., Nissinen, A., 2011. Carbon footprint of food e approaches from national inputeoutput statistics and a LCA of a food portion. J. Cleaner Prod. 19, 1849–1856. Valli, E., Manzini, R., Accorsi, R., Bortolini, M., Gamberi, M., Bendini, A., Lercker, G., Toschi, T.G., 2011. Some suggestions for the producers after the simulation of an oil journey: the risk can be oxidation. The Food Supply Chain project at Bologna University. Proceedings of the First International Workshop on Food Supply Chain. Bertinoro (FC) – Orvieto (TN), Italy. Van der Vorst, J.G.A.J., Tromp, S.O., van der Zee, D.J., 2009. Simulation modelling for food supply chain redesign; integrated decision making on product quality, sustainability and logistics. Int. J. Prod. Res. 47 (23), 6611–6631. Viau, M.A., Trepanier, M., Baptiste, P., 2009. Integration of inventory and transportation decisions in decentralised supply chains. Int. J. Logistics Syst. Manage. 5 (3/4), 249–272. Wang, X., Li, D., Li, L., 2009. Adding value of food traceability to the business: a supply chain management approach. Int. J. Serv. Oper. Inf. 4 (3), 232–257. Xia, B., Sun, D., 2002. Applications of computational fluid dynamics (CFD) in the food industry: a review. Comput. Electron. Agric. 34, 5–24. Xiang Ming, Eschke, R., 2004. Modelling of the effects of continual shock loads in the transport process. Packaging Technol. Sci. 17 (1), 31–35. Yu, H.-F., Wang, D.-W., 2006. Food-chain algorithm and its application to optimizing distribution network. Dongbei Daxue Xuebao/J. Northeastern Univ. 27 (2), 146– 149. Zhang, J., Liu, L., Mu, W., Moga, L.M., Zhang, X., 2009. Development of temperaturemanaged traceability system for frozen and chilled food during storage and transportation. J. Food Agric Environ. 7 (3&4), 28–31. Zhu, X., Mukhopadhyay, S.K., Kurata, H., 2012. A review of RFID technology and its managerial applications in different industries. J. Eng. Technol. Manage. 29, 152, 16 Fine modulo.