Late customisation: issues of mass customisation in the food industry

McIntosh, R I; Matthews, Jason; Mullineux, Glen; Medland, A J

doi:10.1080/00207540802577938

Cited by 69 publications

(72 citation statements)

References 38 publications

(25 reference statements)

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“…So far, the applications of MC in some sectors, e.g. food industry [60], electronics [61], large engineered products [62], mobile phones [63] and personalized nutrition [64] have been dominating their competition. Some special MC applications have been presented in homebuilding [65] and the production of foot orthoses [66].…”

Section: Mass Customizationmentioning

confidence: 99%

Automated process planning and cost estimation under material quality uncertainty

Huang

Chaiprapat

Waiyagan

2015

Int J Adv Manuf Technol

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Section: Mass Customizationmentioning

confidence: 99%

Automated process planning and cost estimation under material quality uncertainty

Huang

Chaiprapat

Waiyagan

2015

Int J Adv Manuf Technol

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“…Cleaning is an important part of the set-up time in PIs. Based on the type of industry, for example, in food or pharmaceutical industries, it can account for up to 50% of labor losses per set-up (McIntosh, Matthews, Mullineux, & Medland, 2010). Olhager and Rudberg (2002) suggest that in comparison to market and product characteristics, the flow of material and the process choice is less influential at the S&OP level.…”

Section: Sandop and Control Modementioning

confidence: 99%

A modularized framework for sales and operations planning with focus on process industries

Noroozi

Wikner

2016

Production & Manufacturing Research

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This paper suggests a modularized sales and operations planning (S&OP) framework, consisting of content and process. The framework's content is based on a typology of decoupling points in which the effect of decoupling points on the decision variables in S&OP is studied. The framework's process takes a step back and addresses the need for a more elaborate design to precede the operational use of S&OP content for different production contexts. The framework supports both process industries (PIs) and discrete manufacturing industries (DIs), and recognizes their specific requirements and reflects them in their S&OP. The differentiating characteristics of PIs and DIs are emphasized through three different decoupling points, namely: discretization decoupling point, control mode decoupling point, and customer order decoupling point. The suggested framework aims to fill the gap in the literature regarding the lack of aggregate planning processes that match the PIs' specific requirements by reflecting the differentiating characteristics of PIs in S&OP.

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“…combined MTS-MTO such as ATO/FTO (Soman, et al, 2004) by moving CODP upstream for MTS or adding customized operations in the downstream (Hoekstra & Romme, 1992). Postponement strategy practice in process industries though lags behind the discrete manufacturers (McIntosh, et al, 2010) due to the cost of low utilization of equipment, the possibility of decoupling the production process and Chapter: Frame of references adding buffers, the capacity of the buffers and the selection of intermediate products (Van Hoek, 1999) (Caux, et al, 2006) (Akkerman, et al, 2010) (Sharda & Akiya, 2012) (Kilic, et al, 2013).…”

Section: Driver Typementioning

confidence: 99%

“…Set-up time is crucial for process industries and specifically the continuous production since for these companies set-ups are long and partly sequence-dependent (Taylor & Bolander, 1994) (Van Donk, 2001) (McIntosh, et al, 2010). Cleaning is an important part of the set-up time especially in food or pharmaceutical industries (ibid).…”

Section: Chapter: Frame Of Referencesmentioning

confidence: 99%

A Framework for Sales and Operations Planning in Process Industries

Noroozi¹

2014

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This thesis studies Sales and Operations Planning (S&OP) in process industries. S&OP is a planning process which has a role of balancing demand and supply at an aggregate level. S&OP has traditionally been considered as a generic process meaning that it is independent from the context of the industry in which it is implemented. Process industries do; however, have specific characteristics which affect their planning and control processes, including S&OP. Therefore, the aim in this thesis is to reconcile these two contradictory stances and furthermore investigate how the specific properties in process industries should be included into an S&OP framework. Such a differentiated framework aims to support process industries to design/implement their S&OP process based on their unique requirements in relation to their markets, products and processes while it also takes into account the specific characteristics regarding the continuous production. Consequently, the process industries would realize the expected benefits from S&OP process to a greater extent.The study starts with a literature review on S&OP in process industries in order to build the knowledge foundation for subsequent studies. The results show that the underlying difference between process industries and discrete industries is the object continuity which affects the selection of production processes including resources. Thus, process industries are often hybrids in the sense that their production processes include both continuous production, when the transformed object (material) is continuous, and discrete production when the object (material) turns into discrete products after the discretization point. In other words, process industries deploy both continuous production and discrete production while discrete industries use only discrete production. The specific characteristics of process industries are actually related to the continuous production part and influence the planning processes as well. As the result of this study, the continuous production characteristics that can affect the S&OP process are identified.In the continuation of the thesis and in order to provide a typology for planning and control purposes, the object type (continuous and discrete) is combined with two other dimensions i.e. mode type (onetime, intermittent and continuous) and driver type (customer order driven and forecast driven) into a planning and control typology. The mode type addresses the repetitivity of the flow and the driver type takes into account the trigger of the flow. Each dimension has a transition point -i.e. the discretization point for the object type, mode interface point for the mode type and customer order decoupling point for the driver typeand represents a hybrid situation since different production environments are required before and after each transition point. The typology aims to illustrate how each dimension affects the planning and control issues as well as how the dimensions are interrelated and how this combination influence the manage...

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Late customisation: issues of mass customisation in the food industry

Cited by 69 publications

References 38 publications

Automated process planning and cost estimation under material quality uncertainty

Automated process planning and cost estimation under material quality uncertainty

A modularized framework for sales and operations planning with focus on process industries

A Framework for Sales and Operations Planning in Process Industries

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