Design and control of food job-shop processing systems. A simulation analysis in the catering industry

• Pages: 782-797
• Published date: 14 August 2017
• Date: 14 August 2017
• DOI: https://doi.org/10.1108/IJLM-11-2015-0204
• Author: Stefano Penazzi,Riccardo Accorsi,Emilio Ferrari,Riccardo Manzini,Simon Dunstall
• Subject Matter: Management science & operations,Logistics

Design and control of food

job-shop processing systems

A simulation analysis in the catering industry

Stefano Penazzi, Riccardo Accorsi, Emilio Ferrari and

Riccardo Manzini

Department of Industrial Engineering, University of Bologna, Bologna, Italy, and

Simon Dunstall

Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO),

Melbourne, Australia

Abstract

Purpose –The food processing industry is growing with retail and catering supply chains. With the rising

complexity of food products and the need to address food customization expectations, food processing

systems are progressively shifting from production line to job-shops that are characterized by high flexibility

and high complexity. A food job-shop system processes multiple items (i.e. raw ingredients, toppings,

dressings) according to their working cycles in a typical resource and capacity constrained environment.

Given the complexity of such systems, there are divergent goals of process cost optimization and of food

quality and safety preservation. These goals deserve integration at both an operational and a strategic

decisional perspective. The twofold purpose of this paper is to design a simulation model for food job-shop

processing and to build understanding of the extant relationships between food flows and processing

equipment through a real case study from the catering industry.

Design/methodology/approach –The authors designed a simulation tool enabling the analysis of food

job-shop processing systems. A methodology based on discrete event simulation is developed to study the

dynamics and behaviour of the processing systems according to an event-driven approach. The proposed

conceptual model builds upon a comprehensive set of variables and key performance indicators (KPIs) that

describe and measure the dynamics of the food job-shop according to a multi-disciplinary perspective.

Findings –This simulation ident ifies the job-shop bot tlenecks and investiga tes the utilization o f the

working centres and produ ct queuing through the system. This approac h helps to characterize how costs

are allocated in a flow- driven approach and identifies the trade-off between in vestments in equipment and

operative costs.

Originality/value –The primary purpose of the proposed model relies on the definition of standard

resources and operating patterns that can meet the behaviour of a wide variety of food processing equipment

and tasks, thereby addressing the complexity of a food job-shop. The proposed methodology enables the

integration of strategic and operative decisions between several company departments. The KPIs enable

identification of the benchmark system, tracking the system performance via multi-scenario what-if

simulations, and suggesting improvements through short-term (e.g. tasks scheduling, dispatching rules),

mid-term (e.g. recipes review), or long-term (e.g. re-layout, working centres number) levers.

Keywords Food processing, Simulation, Food industry, Catering industry, Job-shop system

Paper type Research paper

1. Introduction

The food and drink industry is the largest manufacturing sector in the EU (14.6 per cent of

GDP in 2014) with a turnover of €1.048 billion and employs 4.2 million people in

approximately 286,000 companies, mostly small and medium enterprises (Food Drink

Europe Data and Trends, 2014).

The development of this sector follows the evolving trends of food habits and consumer

expectations (Hollingsworth, 2003). The growth of potential new markets for safer, healthier,

and higher quality food leads practitioners to re-think and re-design the traditional food

processing systems and operations to cope with consumer needs (Zokaei and Simons, 2006;

Khan et al., 2013; Wu et al., 2015). In lieu of standardized food products, a growing segment

The International Journal of

Logistics Management

Vol. 28 No. 3, 2017

pp. 782-797

© Emerald PublishingLimited

0957-4093

DOI 10.1108/IJLM-11-2015-0204

Received 4 November 2015

Revised 21 July 2016

9 November 2016

Accepted 9 November 2016

The current issue and full text archive of this journal is available on Emerald Insight at:

www.emeraldinsight.com/0957-4093.htm

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IJLM

28,3

of consumers push for customized food items that provide nutrition and a better sensory

experience and prevents illnesses and chronic pathologies (Regmi and Gehlhar, 2005).

In order to address this demand and create value-driven food supply chains, the food

industry has to re-align its production systems and operations with advanced technologies

and procedures enhancing both efficiency and flexibility (Bourlakis et al., 2012). The

variability of food items depends on many factors, including their nature (e.g. solid, liquid,

paste), their processing (e.g. assembling, mixing, slicing, mincing, cooking, freezing), their

properties (e.g. density, viscosity, texture, geometry), and their value (Matthews et al., 2007).

The complexity of food processing is further increased by the seasonality of both supply

and customer demand (Taylor, 2006) and the ability to handle this variability with the

increasing production mix.

To achieve higher flexibility in handling the increased production mix, the processing

systems are progressively shifting from flow-line production systems to job-shop systems

(Curt et al., 2007). The design and management of food job-shops involves integrated and

challenging issues dealing with long-term decisions (e.g. the plant layout, the processing

equipment), mid- and short-term decisions (e.g. the definition of the production mix, the

recipes and the related working cycle), and operational daily decisions. Operational

decisions range from the scheduling of the processing tasks to comply with demand or

technical priorities, labour and equipment availability, and safety limitations.

A food job-shop system processes multiple items (i.e. raw ingredients, toppings,

dressings) according to their working cycles in a typical resource and capacity constrained

environment. The generic working cycle results in multiple concurrent and non-concurrent

tasks, performed in manual and/or automatic working stations. Given the increased

complexity of such systems, the divergent goals of process cost optimization and of food

quality and safety preserving require integration at both the operational and the strategic

decision making perspective. These decisions may include determining the size and type of

the processing equipment, planning the facility layout, scheduling the processing activities,

allocating the labour capacity, establishing buffers, and implementing hazard analysis and

critical control points protocols.

While such decisions are generally allocated to various departments (e.g. production

planners, the quality department, plant engineering, sales), their insight interdependency

critically affects the efficiency of the production process. Decision-support tools based on

optimization or simulation techniques, as well as implementation of integrated management

models, are therefore necessary to join divergent expertise, methodologies, and objectives

underlining the food job-shop.

This paper explores the application of simulation modelling to understand the dynamic

behaviour of a food job-shop processing system. The twofold aim of this paper is to design a

simulation model for food job-shop processing and to build the understanding of the extant

relationships between food flows and processing equipment through a real case study from

the catering industry. The results highlight the role of the proposed methodology in

supporting the assessment of bottlenecks, as well the re-design of the processing equipment

and their layout given both the bounds of the process and the product features.

The applicationof simulation techniquesto study the dynamics of foodsystems has a long

tradition.Using computer-aided processengineering, Saravacosand Kostaropoulos (1996) and

Gulati and Datta (2013) review the equations describing the physical, mechanical, thermal,

drying, electrical phenomena, andrelated parameters to be implementedinto simulation tools.

Close to these contributions, Lemus-Mondaca et al. (2011) explore the role of simulation

coupled with physical experiments and analytical solutions in enhancing the knowledge on

heat transfer in foodprocessing. Simulation is indeedvery popular in aiding food engineering

(Saguy et al., 2013; Datta, 2016) since understanding the food physics phenomena in depth is

not still possible solely via empirical methods.

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Food job-shop

processing

systems