Economies of collaboration in build‐to‐model operations

• Author: Xun Wang,Stephen M. Disney,Jan Holmström,Daniel R. Eyers,Carl Philip T. Hedenstierna,Aris A. Syntetos
• DOI: http://doi.org/10.1002/joom.1014
• Published date: 01 December 2019
• Date: 01 December 2019

RESEARCH ARTICLE

Economies of collaboration in build-to-model operations

Carl Philip T. Hedenstierna

1

| Stephen M. Disney

1

| Daniel R. Eyers

1,2

|

Jan Holmström

3

| Aris A. Syntetos

1,2

| Xun Wang

1,2

1

Logistics Systems Dynamics Group,

Cardiff Business School, Cardiff University,

Cardiff, United Kingdom

2

Panalpina Centre for Manufacturing and

Logistics Research, Cardiff Business School,

Cardiff University, Cardiff, United Kingdom

3

Department of Industrial Engineering and

Management, Aalto University, Aalto,

Finland

Correspondence

Aris A. Syntetos, Panalpina Centre for

Manufacturing and Logistics Research,

Cardiff Business School, Cardiff University,

Aberconway Building, Colum Drive, Cardiff

CF10 3EU, United Kingdom.

Email: syntetosa@cardiff.ac.uk

Handling Editor: Tyson R Browning

Funding information

Innovate UK; Engineering and Physical

Sciences Research Council, Grant/Award

Number: KTP 10165

Abstract

The direct-from-model and tool-less manufacturing process of 3D printing (3DP)

embodies a general-purpose technology, facilitating capacity sharing and outsour-

cing. Starting from a case study of a 3DP company (Shapeways) and a new market

entrant (Panalpina), we develop dynamic practices for partial outsourcing in build-

to-model manufacturing. We propose a new outsourcing scheme, bidirectional par-

tial outsourcing (BPO), where 3D printers share capacity by alternating between

the role of outsourcer and subcontractor based on need. Coupled with order book

smoothing (OBS), where orders are released gradually to production, this provides

3D printers with two distinct ways to manage demand variability. By combining

demand and cost field data with an analytical model, we find that BPO improves

3DP cost efficiency and delivery performance as the number of 3DP firms in the

network increases. OBS is sufficient for an established 3D printer when alternatives

to in-house manufacturing are few, or of limited capacity. Nevertheless, OBS

comes at the cost of reduced responsiveness, whereas BPO shifts the cost and

delivery performance frontier. Our analysis shows how BPO combined with OBS

makes 3DP companies more resilient to downward movements in both demand

and price levels.

KEYWORDS

3D printing, build-to-model, capacity sharing, design science research, empirical study, general

purpose technology, order book smoothing

1|INTRODUCTION

3D printing (3DP) technology changes the relationship

between customersand manufacturers (Tuck, Hague,& Burns,

2007), and has led to some unlikely industrial collaborations.

Being a general-purpose technology (David, 1990), 3DP is

used for manufacturing prototypes, tools, customized compo-

nents, complex final parts, and spare parts (Garrett, 2014;

Holmström, Liotta, & Chaudhuri, 2017). Parts are fabricated

directly from 3D design files that can be sent electronically to

any manufacturer for production, quickly, at low transaction

cost. These characteristics allow foron-demand manufacturing

and design customization (Deradjat & Minshall, 2017;

Ottmeier & Hofmann,2016), and for combining multipleparts

(kits) into a single build (Achillas, Aidonis, Iakovou, Thymia-

nidis, & Tzetzis,2015; Ruffo, Tuck, & Hague,2006).

In contrast to using conventional make-to-order, where

supply chains are designed for a specific product type,compa-

nies may opt for a build-to-model mode of manufacturing,

where general-purpose equipment makes it possible to delay

the choice of manufacturer until the day of production. Cur-

rent build-to-model practices involve designers uploading

Received: 16 May 2017 Revised: 30 November 2018 Accepted: 26 January 2019

DOI: 10.1002/joom.1014

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original

work is properly cited.

© 2019 The Authors. Journal of Operations Management published by Wiley Periodicals, Inc. on behalf of The Association for Supply Chain Management Inc.

J Oper Manag. 2019;65:753–773. wileyonlinelibrary.com/journal/joom 753

their data files to a preselected manufacturer's website, or

requesting bids in electronic marketplaces (Eyers & Potter,

2015). Manufacturers may also exploitbuild-to-model by tak-

ing on more orders than in-house capacity permits, as both

outsourcing and accepting subcontractwork is easy compared

to conventional production given that no customer-specific

tooling (jigs, fixtures, etc.) is used (Baumers et al., 2013).

While customers may not be too concerned with the selection

of manufacturer, the manufacturing location and lead time are

often essential. The homogeneity of 3DP technology makes it

possible to select manufacturers close to the end customer

(Khajavi, Partanen, & Holmström, 2014), while at the same

time, manufacturers with assembly operations are motivated

to possess in-house 3DP to reap the benefits of reduced han-

dling, warehousing, and simplified assembly operations

(Khajavi et al., 2018; Lyly-Yrjänäinen, Holmström, Johans-

son, & Suomala, 2016). Thus, a 3DP company can be both a

customer and a provider of 3DP services.

Using a build-to-model 3DP case, we investigate how

collaborative outsourcing practices compare to pure in-house

production or outsourcing. We demonstrate that companies

profit from partial outsourcing by maintaining capacity while

engaging in outsourcing (Gray, Tomlin, & Roth, 2009). The

outsourcing arrangement can be unidirectional partial out-

sourcing (UPO), occasionally shifting peak demand to sub-

contractors. Another mechanism is bidirectional partial

outsourcing (BPO), where peak demand is outsourced, and

slack capacity is offered to other firms. In this setting, each

decision to outsource is an on-going operational decision,

rather than a one-off strategic decision. Every time a surplus

demand at one firm is matched with spare capacity at

another, both profit from the trade and economies of collab-

oration are realized. The effect is comparable to variability

pooling but does not require any centralization, as decentra-

lized orders and capacity are traded between firms. Notably,

partial outsourcing takes the variability of production

requirements and diminishes their economic impact. To put

this into context, we also investigate the effect of order book

smoothing (OBS), which reduces the variability of orders

before they reach production. OBS works by holding orders

in an order book, allowing for job releases onto the shop

floor at a rate steadier than demand, reducing the need for

surge capacity from subcontractors. Table 1 summarizes the

central concepts in this paper.

We use a multimethod approach that combines design sci-

ence and case research with analytical modeling. A 3DP case

study describes the collaboration between Shapeways and

Panalpina World Transport Ltd. from 2014 to 2016. Shape-

ways is the world's leading on-line 3DP service, community,

and marketplace. The company operates two 3DP factories,

one in New York, the other in Eindhoven. As a third-party

logistics provider, Panalpina providestraditional air and ocean

freight solutions. To distinguish itself in the market, Panalpina

also offers a range of logistics manufacturing services, one

of these being 3DP. At the time of this research, Panalpina

conducted their 3DP in Eindhoven; the collaboration with

Shapeways facilitated their entry into the 3DP industry. Sha-

peways directs demand beyond their in-house capacity to a

network of subcontractors, one of which is Panalpina World

Transport Ltd.

We emphasize that a network of 3D printers differs from

a supply chain of conventional manufacturers (Ben-Ner &

Siemsen, 2017; d'Aveni, 2015) which we can understand via

the performance frontier concept. The performance frontier

(Schmenner & Swink, 1998; Vastag, 2000) distinguishes

between the performance that is possible in principle (the

asset frontier defined by the technology), and the perfor-

mance achieved (the operations frontier defined by the avail-

able operational practices). Operating as a conventional

supply chain leads to performance that is far from the asset

frontier. Moving 3DP performance towards what is possible-

in-principle requires new operational practices that account

for 3DP characteristics, such as practices enabling capacity

pooling (Khajavi & Holmström, 2017). The success of 3DP

capacity pooling is measured by profit (or the reduction of

avoidable costs) and responsiveness (lead time for the cus-

tomer), defining a new operational frontier.

The literature disagrees about the future role of 3DP in

supply chains, with some authors suggesting that 3DP

enables vastly simplified supply chains (Mellor, Hao, &

Zhang, 2014), while others highlight the possibility of

TABLE 1 Central concepts in the paper and their definitions

Concept Description

Build-to-model A manufacturing mode using the

product design model for direct

control of manufacturing, assembly,

and logistics. General purpose

resources add value as specified in the

design model without set-up

Order book

smoothing (OBS)

A practice for reducing the variability of

production. The order book acts as a

time buffer

Unidirectional partial

outsourcing (UPO)

A strategy for reducing the impact of

production variability. Base demand

is managed by in-house capacity;

peak demands are outsourced to

another company. The outsourcing is

unidirectional

Bidirectional partial

outsourcing (BPO)

A strategy for reducing the impact of

production variability. Firms alternate

between roles as outsourcer and

subcontractor. The outsourcing is

bidirectional

754 HEDENSTIERNA ET AL.