Renzo Akkerman

Quality, safety and sustainability in food distribution: A review of quantitative operations management approaches and challenges

The management of food distribution networks is receiving more and more attention, both in practice and in the scientific literature. In this paper, we review quantitative operations management approaches to food distribution management, and relate this to challenges faced by the industry. Here, our main focus is on three aspects: food quality, food safety, and sustainability. We discuss the literature on three decision levels: strategic network design, tactical network planning, and operational transportation planning. For each of these, we survey the research contributions, discuss the state of the art, and identify challenges for future research.

Opportunities and realities of supply chain integration: the case of food manufacturers

Purpose – The purpose of the paper is to investigate the limitations and barriers for supply chain integration that food manufacturers experience and to highlight their planning and scheduling problems. Possible ways to cope with these are offered.Design/methodology/approach – The paper is theoretical/conceptual in nature: the findings are illustrated in an explorative case study.Findings – It is often suggested that food supply chains are typical for what can be achieved in supply chain management. This paper challenges this belief by investigating the possibilities and limitations for supply chain integration for food manufacturers. The authors argue that a combination of typical food characteristics and the use of shared resources limit the possibility for integration, while uncertainties and complex business conditions increase the need for integration. In a case study, the paper explores alternatives to cope with that situation.Research limitations/implications – The paper is based on previous empiri...

SKU classification: a literature review and conceptual framework

Purpose – Stock keeping unit (SKU) classifications are widely used in the field of production and operations management. Although many theoretical and practical examples of classifications exist, there are no overviews of the current literature, and general guidelines are lacking with respect to method selection for classifying SKUs. The purpose of this paper is to systematically synthesise the earlier work in this area, and to conceptualise and discuss the factors that influence the choice of a specific SKU classification.Design/methodology/approach – The paper structurally reviews existing contributions and synthesises these into a conceptual framework for SKU classification.Findings – How SKUs are classified depends on the classification aim, the context and the method that is chosen. In total, three main production and operations management aims were found: inventory management, forecasting and production strategy. Within the method three decisions are identified to come to a classification: the chara...

Make to stock and mix to order: choosing intermediate products in the food-processing industry

In contrast to discrete manufacturers, food-processing companies can sometimes produce the same end products in different ways: either mix first and then process, or process first and mix later. Moreover, a final product can be mixed from different raw materials or intermediates. That adds a new dimension to postponement and decoupling point theory as choices need to be made not only with regard to where to locate inventory, but also which products to store. That aspect has not been covered so far. This paper explores this problem for a typical two-stage food production situation in a flour mill. The number and composition of intermediate products in the decoupling point is determined using a stepwise solution approach supported by mathematical programming models. The procedure facilitates decision-making for the management of the mill regarding how many and what intermediates to store. Extensions of the models presented might be helpful to solve related problems such as determining the number of intermediate storage tanks required.

Analyzing scheduling in the food-processing industry: structure and tasks

Production scheduling has been widely studied in several research areas, resulting in a large number of methods, prescriptions, and approaches. However, the impact on scheduling practice seems relatively low. This is also the case in the food-processing industry, where industry-specific characteristics induce specific and complex scheduling problems. Based on ideas about decomposition of the scheduling task and the production process, we develop an analysis methodology for scheduling problems in food processing. This combines an analysis of structural (technological) elements of the production process with an analysis of the tasks of the scheduler. This helps to understand, describe, and structure scheduling problems in food processing, and forms a basis for improving scheduling and applying methods developed in literature. It also helps in evaluating the organisational structures and information flows related to scheduling.

Influence of capacity- and time-constrained intermediate storage in two-stage food production systems

In food processing, two-stage production systems with a batch processor in the first stage and packaging lines in the second stage are common and mostly separated by capacity- and time-constrained intermediate storage. This combination of constraints is common in practice, but the literature hardly pays any attention to this. In this paper, we show how various capacity and time constraints influence the performance of a specific two-stage system. We study the effects of several basic scheduling and sequencing rules in the presence of these constraints in order to learn the characteristics of systems like this. Contrary to the common sense in operations management, the LPT rule is able to maximize the total production volume per day. Furthermore, we show that adding one tank has considerable effects. Finally, we conclude that the optimal setup frequency for batches in the first stage is dictated by the storage time constraint.

Procurement planning in oil refining industries considering blending operations

This paper addresses procurement planning in oil refining, which has until now only had limited attention in the literature. We introduce a mixed integer nonlinear programming (MINLP) model and develop a novel two-stage solution approach, which aims at computational efficiency while addressing the problems due to discrepancies between a non-linear and a linearized formulation. The proposed model covers realistic settings by allowing the blending of crude oil in storage tanks, by modeling storage tanks and relevant processing units individually, and by handling more crude oil types and quality parameters than in previous literature. The developed approach is tested using historical data from Statoil A/S as well as through a comprehensive numerical analysis. The approach generates a feasible procurement plan within acceptable computation time, is able to quickly adjust an existing plan to take advantage of individual procurement opportunities, and can be used within a rolling time horizon scheme.

Logistics network design for perishable products with heterogeneous quality decay

The duration of logistics operations, as well as the environmental conditions during these operations, significantly impact the performance of a logistics network for fresh agricultural products. When durations or temperatures increase, product quality decreases and more effort is required to deliver products in time and with the right quality. Different network designs lead to different durations and conditions of transport, storage, processing, etc. Therefore, when making network design decisions, consequences for lead time and product quality should be taken into account. As decay of perishable products, for instance food, is often not uniform, heterogeneity in product quality decay also has to be considered. The aim of this paper is to show how product quality decay as well as its heterogeneity can be integrated in a network design model. A new mixed integer linear programming formulation is presented, which positions stocks and allocates processes to maximise profit under quality constraints. It is applied to several test instances from the horticultural sector. Results show that different levels of decay lead to different network structures. Changing decay rates due to processing particularly affect the level of postponement. Heterogeneity in product quality causes a split in product flows with high and low product quality. All in all, it is shown that heterogeneous product quality decay should be taken into account in network design as it significantly influences network designs and their profitability, especially when the supply chain includes processes that change the level of decay, and product quality differences can be exploited in serving different markets.

MILP approaches to sustainable production and distribution of meal elements

This paper studies the production and distribution system for professionally prepared meals, in which a new innovative concept is applied. The concept aims to improve the sustainability of the system by distributing meal elements super-chilled in the conventional cold chain. Here, sustainability comprises economic, environmental and social aspects. The impacts on and trade-offs between the different dimensions of sustainability are discussed, and combined with aspect of product quality. Furthermore, we identify the important planning decisions in relation to production and distribution and organise these in a decision hierarchy. Based on these discussions, decision support models based on mixed-integer linear programming are developed for the planning tasks on the tactical level, including decision-making on packaging options and delivery structures. The resulting models can be used to support production and distribution planning, and also evaluate the performance of and quantify the trade-offs between the different sustainability dimensions.

Decision support in hierarchical planning systems

In this paper, we discuss the development of decision support systems for hierarchically structured planning approaches, such as commercially available advanced planning systems. We develop a framework to show how such a decision support system can be designed with the existing organization in mind, and how a decision process and corresponding software can be developed from this basis. Building on well-known hierarchical planning concepts, we include the typical anticipation mechanisms used in such systems to be able to decompose planning problems, both from the perspective of the planning problem and from the perspective of the organizational aspects involved. To exemplify and develop our framework, we use a case study of crude oil procurement planning in the refining industry. The results of the case study indicate an improved organizational embedding of the DSS, leading to significant savings in terms of planning efforts and procurement costs. In general, our framework aims to support the continuous improvement of advanced planning systems, increasing planning quality in complex supply chain settings. DSS development in the context of hierarchical planning systemsInclusion of organizational considerations in DSS developmentEmbedding of hierarchical planning aspects in problem decompositionDSS development consists equally of organization, process, and software design.Case study of crude oil procurement planning for refining industries