University of Groningen

(1)

University of Groningen

Faculty of Economics and Business

Master Thesis – Technology & Operations Management

A unified framework of designing Pull Production Control Systems: A

systematic literature review

Author: Supervisor:

Marina Karpenko - S3045048 N. Ziengs, MSc.

(2)

Abstract

Purpose: Large number of papers about pull production control systems (PPCS) have been

published. These papers have documented a great number of different variations of PPCS, which are applicable for different situations in manufacturing. PPCS differ in terms of design characteristics making a certain system more applicable for particular circumstances. Those aspects can be combined to create new systems which fit specific manufacturing environments. However, until now, there is no classification of PPCS based on their characteristics. A classification is established to determine which PPCS is assigned to be most effective in certain environmental conditions. The classification supports the ease of developing new PPCS or customizing old ones.

Methodology: A systematic literature review (SLR) method is used. A total of 70 papers was

retrieved, studied and analyzed. Deductive coding for already established categorizations and inductive coding for new categorizations is applied to develop the classification and framework.

Findings: Based on the analysis, a framework is developed which aids configuring PPCS for

specific needs of a manufacturing company.

Originality/Value: This thesis aims to give an overview of which PPCS have been studied and

to provide directions on where future research should focus on. Moreover, the paper provides guidance for practitioners and academics to choose and design a PPCS that is most effective in certain environmental conditions.

(3)

List of Abbreviations

CTBS Customized Token Based System

EDD Earliest Due Date

FCFS First Come First Serve

GFS General Flow Shop

GJS General Job Shop

GKCS Generic Kanban Control System

KCS Kanban Control System

MTO Make-To-Order

MTS Make-To-Stock

PA Product Anonymous

PFS Pure Flow Shop

PJS Pure Job Shop

PPC Production Planning and Control

PPCS Pull Production Control Systems

PS Product Specific

TH Throughput

TTT Total Throughput Time

SL Service Level

SLR Systematic Literature Review

SPT Shortest Processing Time

STT Shop Floor Throughput Time

(4)

Table of Figures

Figure 2.1 PPC Rule ,TTT, and STT (Fredendall et al., 2010 and Germs & Riezebos, 2010) ... 3

Figure 2.2 Centralized; Conwip………. ………5

Figure 2.3 Decentralized; KCS ... 5

Figure 2.4 Non-Route Specific; Conwip ... 6

Figure 2.5 Route Specific; M-Conwip ... 6

Figure 2.6 Possible Control Loops; Polca... 7

Figure 2.7 Single Card System (González-R et al., 2012) ... 9

Figure 2.8 Dual Card System (González-R et al., 2012) ... 9

Figure 2.9 Product-Specific; KCS (Ziengs et al., 2012) ... 10

Figure 2.10 Product-Anonymous; Conwip (Ziengs et al., 2012) ... 10

Figure 2.11 Unit Based; KCS ... 11

Figure 2.12 Load Based; LB Polca ... 12

Figure 2.13 Overview of Design Aspects ... 12

Figure 2.14 Conceptual Model ... 17

Figure 3.1 Systematic selection of papers on structure and configuration classification (in accordance with van Kampen et al., (2012)) ... 21

Figure 4.1 Configurational Aspects of PPCS ... 30

Figure 4.2 Structural Aspects of PPCS ... 31

Figure 4.3 Above/Below CL (Gaury 2000) ... 33

Figure 4.4 Updated Conceptual Model ... 35

Figure 4.5 PPCS according to Org. Typology & Org. Strategy ... 35

(7)

Figure 4.7 PPCS in MTS & GFS ... 38

Figure 4.8 PPCS in MTO & PFS ... 38

Figure 4.9 PPCS in MTO& GFS; in MTO & PJS; in MTO & GJS ... 39

Figure 4.10 The unified Framework of designing PPCS ... 40

Table of Tables

Table 2.1 Typologies with associated material flow and environment (Stevenson et al., 2005) .. 14

Table 3.1 Selected Database ... 19

Table 4.1 Overview of the PPCS in the literature……… 23

(8)

Preface

This paper represents the final work of my journey in the MSc Program Technology and Operations Management. This period in Groningen truly represents the time with one of the hardest challenges I had so far, but I never learned that much in such a short time.

I would like to express my deepest gratitude to my supervisor Nick Ziengs, who always believed in my work and was never getting tired of leading me to the right path. I would also like to thank to my co assessor Dr. J.A.C., Bokhorst for his great feedback in the initial stage.

Furthermore, I would like to thank my friends and family members for supporting me during my years of study in Bachelor and in Master. Without their encouragement, I would never be able to be at the stage, where I am standing now. Finally, I would like to thank my partner, Stephan, for his outstanding support and appreciation for all my up and downs during these years. Last but not least, my year in the Netherlands would definitely not be the same without Katie, and Hendrik – my learn-, group-, assignment- and thesis buddy. Thank you for always being there for me.

(9)

1. Introduction

An effective production planning and control system is of great importance to most manufacturing companies. Pull systems are often used for production control. An effective pull production control system (PPCS) might make the difference between success and failure of the company (Khojasteh, 2016). PPCS consist of different design elements which decide about the success of performance of the system. Therefore, the choice of the design should match the needs of the manufacturing organization to make the PPCS effective (Akturk & Erhun, 1999). Nevertheless, organizations often opt to use a pull system that they are already familiar with, rather than a system that fits their specific needs (González-R et al., 2012). In this thesis, a framework is developed which aids configuring PPCS for specific needs of a manufacturer.

PPCS aim to avoid unnecessary work in progress (WIP) by explicitly limiting the amount of WIP that is allowed within the system (Hopp & Spearman, 2001). The structural and configurational characteristics make certain PPCS more suitable for particular environment. Structure determines the limitation of WIP, whereas configuration determines the extend of the limitation (Gaury, 2000).

(10)

As such, this paper addresses the need for a unifying framework of PPCS characteristics. First, existing systems with their derivatives are identified. Second, through coding, their distinguishing characteristics are determined. Third, based on the application of these PPCS, the suitability of their characteristics are linked to specific environmental conditions. The outcome is a framework which relates pull system characteristics to specific environmental settings. The framework can be used to identify new systems or combinations of characteristics to be studied by scholars. Moreover, it can also help practitioners with the selection or customization of their own system.

The developed framework is a resume and an extension of classifications proposed in previous works. Whereas previous work only classified pull systems on a single characteristic, we intend to classify PPCS on a number of characteristics resulting in a comprehensive overview. The following research questions are formulated in order to achieve this objective:

1. RQ: “What PPCS have been developed?”

2. RQ: “What are distinguishing characteristics of these PPCS?”

3. RQ: “Which PPCS are most effective in which environmental conditions?”

(11)

2. Background 2.1. Production Control Systems

Due to increasing competitiveness in the global market, many manufacturing organizations are trying to improve their performance. Production Planning and Control (PPC) systems are an important tool to realize shorter throughput times (TTT), improve quality and delivery date adherence as well as reduce costs (Stevenson et al., 2005).

PPC is divided into three parts. First, it contains authorization to start a job (order acceptance). Second, order release of new material to the shop floor, and third, order dispatching through setting priorities for waiting jobs as well as initiating the start of succeeding activities (Germs & Riezebos, 2010). Figure 2.1 in accordance with Fredendall et al. (2010) and Germs & Riezebos (2010) illustrates the PPC Rules, TTT, and STT:

Figure 2.1 PPC Rule ,TTT, and STT (Fredendall et al., 2010 and Germs & Riezebos, 2010)

2.2. Pull Production Control Systems

(12)

the amount of WIP in the shop floor throughout control loops (Ziengs et al., 2012). Control loops can be used to control WIP in single or multiple workstations (Khojasteh, 2016 and Hopp & Spearman, 2001). The placement of the loops can influence the performance of total throughput time (TTT) and shop floor throughput time (STT) (Germs & Riezebos, 2010).

The difference between push and pull production control systems is that the former ones do not explicitly limit the amount of workload that can be in the system (Hopp & Spearman, 2004). Push systems are usually designed to reach a predefined target level of forecasted demands. They release the material to the shop at a constant rate, or according to a predefined schedule to make use of forecast for future demand (Gstettner & Kuhn, 1996 and González-R et al., 2012).

2.3. Structure & Configuration of Pull Production Control System

(13)

Structure

(1) Centralized VS. Decentralized

A structure is centralized, when the system has only one control loop. When the last workstation request parts, raw materials are released into the production system. Therefore, the one control loop limits the workload on the shop floor (Gaury, 2000). Figure 2.2 shows a centralized structure presented by the example of Conwip (Spearman, 1989). In contrast, a system that is controlled with more loops, is referred to be decentralized (Stevenson et al., 2005). Figure 2.3 presents such a structure by the example of Kanban Control System (KCS) (Sugimori, et al., 1977). The control loops are represented through the dashed line(s). The workstations are named A, B,.. etc. The rectangles represent queues.

Figure 2.2 Centralized; Conwip Figure 2.3 Decentralized; KCS

(14)

(2) Route Specific VS. Non-route specific

The design aspect route specific can only occur, if multiple routings are present. Environments with single stage or line are non-route specific. In the case of non-route specific control, one control loop is used for the whole shop floor. Conwip is an example of non-route specific system as illustrated in figure 2.4 (Germs & Riezebos, 2010). In contrast, in route specific control, a control loop is used for every possible routing on the shop floor. M-Conwip (Germs & Riezebos, 2010) is an example of route specific PPCS and is illustrated in figure 2.5 (Germs & Riezebos, 2010).

Figure 2.4 Non-Route Specific; Conwip Figure 2.5 Route Specific; M-Conwip

(15)

(3) Overlapping VS. Non-overlapping control loops

In non-overlapping control loops, there is a single loop per workstation (Gaury, 2000). Once again, Conwip in figures 2.2, 2.4. is an example. In contrast, overlapping control loops are controlled by multiple loops per workstation. Overlapping loops can be used for orders that need to visit more than two workstations (Germs & Riezebos, 2010). Figure 2.6 illustrates Polca (Riezebos, 2010). The control loops for workstation B are overlapping due to the fact that it is controlled by different control loops. All the other sequences represent non-overlapping control loops.

Figure 2.6 Possible Control Loops; Polca

(16)

Configuration

After a structure is chosen, the next step is to decide how many and what type(s) of cards should be assigned to each control loop. The number of cards controls the amount of work in the system (Gaury, 2000). Well known configurational design aspects are single/dual-card (Berkley, 1992), product anonymous/specific (Riezebos, 2010) and load/unit based (Germs & Riezebos, 2010).

(1) Single Vs. Dual System

PPCS are usually classified in the literature into two different types: single-/ and dual-card systems. In a production process, the material-handling operation between two stations can be performed instantaneous if these stations are located close to each other. In this case, for this pair of workstations, a single inventory buffer and therefore single card system is required (Berkley, 1992). Transportation cards control the material in single-card systems. Transportation cards define the quantity that the succeeding stage should withdraw from the preceding stage (Akturk & Erhun, 1999). Figure 2.7. illustrates such a system.

(17)

input and output buffers. The squares illustrate machines in the production line and the dotted lines are control loops.

Figure 2.7 Single Card System (González-R et al., 2012)

Figure 2.8 Dual Card System (González-R et al., 2012)

Single-card systems are simpler to use and to implement, and have shorter information lead times rather than dual-card systems. On the other side, dual-card systems provide strong control on the production system. But, due to its strict assumptions and prerequisites, they are more difficult to implement (Akturk & Erhun, 1999).

(2) Product – specific vs Product – anonymous

(18)

illustrated in graphic 2.10. Numbers within the cards, which are illustrated through small squares, indicate the control loop to which the card belongs. Shaded cards are product-specific cards and dedicated to their corresponding orders. Cards with dark shade represent product-anonymous cards (Riezebos, 2010 and Ziengs et al., 2012).

Figure 2.9 Product-Specific; KCS (Ziengs et al., 2012)

Figure 2.10 Product-Anonymous; Conwip (Ziengs et al., 2012)

(19)

product-specific is more suitable for MTS organization strategy. In contrast, product-anonymous control progresses orders with the increased product and route variety (Ziengs et al., 2012).

(3) Load based vs Unit based

The next classification is about load and unit based pull systems. Unit based systems control the number of orders on the shop floor. Here, a card represents a single order. Load based PPCS limit the workload based on the work content of orders. KCS is an example of unit based system (Germs & Riezebos, 2010). It is illustrated in the figure 2.11. Load-Based Polca (LBPolca) (Vandaele et al., 2008) represents an example of a load based system and displayed in the figure 2.12. Big orders are represented through a large circle, whereas small orders through small circles. In unit-based systems a card is attached to each order whereas in load-based, a card is attached to a group of orders.

(20)

Figure 2.12 Load Based; LB Polca

In unit based systems the actual processing time requirements of an order are not considered. Therefore, an available card is only a rough approximation of the available capacity. However, systems with that configurational aspect are simpler in handling (Ziengs et al., 2012). In contrast, a card in load based systems represents a predetermined amount of work by taking the processing times requirements of orders into account. Consequently, load based systems are more precise, but are more complicated to handle (Ziengs et al., 2012).

In summary, PPCS can be designed through three structural and three configurational aspects with the difference in its complexity. A better overview provides figure 2.13. that summarizes two combinations. Combination 1 is easier to manage and to implement than combination 2.

(21)

2.3.1. Performance Attainment: Organizational Strategy, Typology & Environment

The organizational environment, namely time variability, arrival variability, routing variability and product variability with its involved set-up times, plays a very important role in choosing the right control system. A poor decision on choosing a not suitable solution, can lead to waste of time and to high expenses (Stevenson et al., 2005). A solution is suitable when a PPCS reaches the desired performance. To achieve a certain performance, PPCS users should first examine their organizational strategy, typology and environment. Afterwards, for a given environment, the optimal set-up of structure and configuration should be found (Gaury, 2000).

Organizational Strategy

Company´s environment can differ between Make-To-Stock (MTS) and Make-To-Order (MTO). MTS environments are characterized by having higher predictability of ordered products with higher levels of repeated business. In contrast, in a MTO sector, the products are driven by customized demand resulting in higher lead times (Stevenson et al., 2005).

Organizational Typology

(22)

Table 2.3.1 Typologies with associated material flow and environment (Stevenson et al., 2005)

Typology Material Flow

Pure Flow Shop (PFS) - Work travels in one direction through a sequence of work centers in a district order

General Flow Shop (GFP) - Work travels in one direction

- but jobs are allowed to visit a subset of work centers

 Permits a limited customization Pure Job Shop (PJB) - Routing sequences are random

- Jobs can start and finish at any work center  Allows complete freedom & customization General Job Shop (GJS) - Provides multidirectional routing

But: with a dominant flow direction

Organizational Environment

The production environment is defined as the set of factors that are not completely controlled by the designer or manager of the production system. This environment includes processing time variability, arrival variability (Gaury, 2000: 13), product- and route variability. Environment or company characteristics affect the performance of the PPCS (Thürer et al., 2016b).

(1) Processing time variability

Cigolini et al. (1998) claim that the processing time variability is one of the most common disturbances in those manufacturing systems where the level of automation is low and equipment is to be carefully managed in order to achieve an effective production control.

(23)

are not predictable, resulting in actual scheduling and shop status to differ over time from the planned schedule (Hopp & Spearman, 2001). Improving the production performance of job shop manufacturing with PPCS supports the effectiveness of reducing set-up, batches and processing time variability, even though the effectiveness varies substantially (J. W. Li, 2003).

(2) Arrival Variability

Arrival variability addresses the varying demand for a single product. The arrival variability outputs at one workstation become highly variable inputs to another workstation. (Hopp & Spearman, 2001: 282). To reduce arrival variability, Hopp & Spearman (2001) suggest to decrease process variability at upstream stations, by using better scheduling and shop floor control to smoothen material flow, eliminate batch releases, reduce transportation and install a pull system.

(3) Routing Variability

Routing variability is defined as a job shop that is characterized by a wide variety of products with variable routings and processing times (Land & Gaalman, 1998: 347). The section “organization typology” in table 2.1. summarizes the different routing versions of routing variability. Some PPCS can help to increase the productivity despite of the large product mix (Riezebos, 2010).

(4) Product Variability & Set-up Times

(24)

is not the case (Krishnamurthy et al., 2004). In addition, when a product variety exists and the material flow is according to a job shop, set-up times could be influential. This aspect is often overlooked in the literature (Li, 2003). This is why, a distinction between single product and product mix is made in this work and set-up times are explicitly considered.

2.3.2. Performance Criteria

To evaluate the applicability of PPCS, performance criteria that are measurable should be defined. In accordance to Gaury (2000), the important performance criteria are WIP and throughput rate (TH). Additionally, many studies are also measuring the TTT and Service Level (SL) (e.g. Sugimori et al., 1977), Bonvik et al., 1997). Consequently, those metrics are also considered in this paper.

2.4. Conceptual Model

(25)

(26)

3. Methodology

In order to develop a classification of PPCS, a systematic literature review (SLR) is conducted. A systematic review adopts a rigorous, well defined, transparent, and replicable process (Thomé et al., 2016). The literature review technique that is used in this paper is based on the approach of Thomé et al. (2016). Other authors like van Kampen et al., (2012) or Buijs et al., (2014) used a similar methodology successfully to conduct their classification of literature.

(1) Literature Search

The unit of analysis for this research is the pull production control system (PPCS) with its structural and configurational aspects, environmental and company setting, typology, and the name of the system. The research paper by Thomé et al. (2016) recommends a seven-step approach to search and select studies as guidance for all SLR. These steps are: 1) Bibliographic database or journals selection, 2) Keywords Search, 3) Review of selected abstracts 4) Application of criteria for inclusion and exclusion of studies 5) Full-text review of selected papers 6) Backward Search, and 7) Forward search in retrieved papers. These steps ensure that all relevant works are included in the review. A similar approach was also successfully used by Buijs et al. (2014), van Kampen et al. (2012), Kamalahmadi & Parast (2016), Tukamuhabwaa et al. (2015) or Thuan et al. (2016) to achieve comparable goals.

(27)

not related to PPCS and those that focused on workforce agility, workforce training, pull systems in supply chains, and the determination of the number of cards. Table 3.1 summarizes the retrieved journal titles from selected databases and the number of papers chosen:

Table 3.1. Selected Database

Journal Titles Databases # of Papers

retrieved

Annals of Operations Research Springer 1

Decision Science Wiley 3

Engineering Costs and Production Economics Science Direct 1

IEE Transactions IEEE 1

IIE Transactions Taylor & Francis 2

International Journal of Business Science and Applied Management

Scopus 1

International Journal of Computer Integrated Manufacturing

Taylor & Francis 1 International Journal of Industrial and Systems

Engineering

Inder Science 1

International Journal of Manufacturing Research Taylor & Francis 1 International Journal of Production Economics Science Direct 6 International Journal of Production Research Taylor & Francis 23

Journal of Intelligent Manufacturing Springer 2

Journal of Operational Research Society JSTOR 1

Management Science Informs 2

Manufacturing & Service Operations Management Informs 1

Naval Research Logistics (NRL) Wiley 1

Operations Research Informs 2

OR Spectrum Springer 1

Production and Operations Management Wiley 6

Production Planning & Control Taylor & Francis 6

Queueing Systems Springer 2

Scientific Bulletin, Automotive Series ICI 1

Thesis Generic 1

Conference/ Hearing Generic 3

24 Journals, 1 Thesis, 1 Conference/ Hearing 10 Databases, 2 Generic

70 Papers

(28)

pull systems, and push and pull. The secondary keywords are related to the methodology (simulation, model). The initial search resulted in 570 papers. As a next step, the abstracts were reviewed and selected to confirm the relevance for the study. This was based on the fact whether the primary and secondary keywords were correlating to each other or not. This step led to the first reduction of relevant papers to a number of 124. Further, the abstracts were reviewed based on the full text of the abstract. At this step 75 papers were selected. After abstract selection, 37 papers were selected for full review. The final selection was made according to the fact, whether or not the paper dealt with the structure and configuration. This step resulted in 18 relevant papers to be reviewed.

(29)

Figure 3.1 Systematic selection of papers on structure and configuration classification (in accordance with van Kampen et al., (2012))

The review is focused on academic papers. Therefore, the possibility of incurring poor-quality and unreliable results in the data analysis is minimized. Nevertheless, a search limitation might occur due to the non-inclusion of grey literature, which might result if non-broadening the information basis with studies of doubtful reliability (Thomé et al., 2016).

(2) Literature Coding

(30)

“non-route-specific”, “overlapping”, “non-overlapping”, “single card”, “dual card”, “product anonymous”, “product specific”, “load based” and “unit based” have been chosen. In addition, new aspects have been derived through inductive coding (“Above/Below Loop”, “Priority Rules_FCFS”, “Priority Rules_EDD”). Here, new findings arose directly from analyzing the literature and are developed into new characteristics. This enabled to extend the conceptual framework.

(31)

4. Results

The goal of this section is to describe the results of each research question derived from the coding and data analysis.

4.1. Results for the Research Question 1

To be able to give an answer to the first RQ (“What PPCS have been developed?”), the selected literature was grouped according to the basic/original system with the related references and its extended systems. Table 4.1. gives an overview of PPCS that were found in the literature:

Table 4.1 Overview of the PPCS in the literature

(32)

Duri_et.al_2000b, Frein_et.al_1995, Karaesmen_Dallery_2000, Koulouriotis_et.al_2010, Generic KCS Chang_Yih_1994a GM_1 Erhun_et.al_2003 GM_2 Gaury_2000, Gaury_et.al_2001 GM_3 Gaury_2000, Gaury_et.al_2001

Hybrid Push/Pull Deleersnyder_et.al_1992, Ghrayeb_et.al_2009 Bonvik_Gershwin_1996, Gaury_et.al_2000, Geraghty_Heavey_2005, Lavoie_et.al_2010 Hybrid Kanban Conwip Hybrid MHCP Hajji_et.al_2009 Job-Shop KCS Gravel_Price_1988 IEKCS Chaouiya_et.al_2000 SEKCS Chaouiya_et.al_2000 PAC Buzacott_Shanthikumar_1992 m-PAC Buzacott_Shanthikumar_1992 reactive Kanban Takahashi_Nakamura_2002

Conwip Claudio_et.al_2010, Claudio_Krishnamurthy_2009, Duri_et.al_2000, Gonzalez-R_Framinan_2009, Gstettner_Kuhn_1996, Koulouriotis_et.al_2010, Lavoie_et.al_2010, Li_2010, Spearman_1992, Spearman_et.al_1990, Spearman_Zazanis_1992, Stevenson_et.al_2005, Thürer_et.al_2016, Yang_2000 2Bound.Hybrid Bonvik_et.al_1997 Conwip Base Stock Rotaru_2011

Conwip-buffer Yang_Hsieh_Cheng_2011 CWIPL Sepehri_Nahavandi_2007 CWIPL II Nahavandi_2009

DEWIP Lödding_et.al_2003

Gated MaxWIP Grosfeld-Nir_Magazine_2002 Hybrid Push/Pull Deleersnyder_et.al_1992,

Ghrayeb_et.al_2009 Bonvik_Gershwin_1996, Gaury_et.al_2000, Geraghty_Heavey_2005, Lavoie_et.al_2010 Hybrid Kanban Conwip Hybrid MHCP Hajji_et.al_2009 M-Closed Conwip Yang_et.al_2011,

Gallien_Wein_2001 m-Conwip Germs_Riezebos_2010

seg.Conwip Gaury_2000, Gaury_et.al_2001, Tayur_1992

Parallel Conwip Prakash_Chin_2011 CONLOAD Rose_1999, Rose_2001,

Liu_2010 CAPWIP Trietsch_2005 Sync. Conwip Takahashi_et al_2005 Reactive Conwip Takahashi_Nakamura_2002 Basestock (BSS) Duri_et.al_2000a Generalized KCS Buzacott_1989,

Duri_et.al_2000a, Duri_et.al_2000b, Frein_et.al_1995,

(33)

Koulouriotis_et.al_2010,

Cobacabana Land_2009, Thürer_et.al_2016

Polca Germs_Riezebos_2010, Krishnamurthy_Suri_2009, Riezebos_2010, Stevenson_et.al_2005, Thürer_et.al_2016 GPolca Fernandes_Carmo-Silva_2006 LB-POLCA Vandaele_et.al_2008

In total, 43 PPCS were found whereby most of the systems are derivatives from KCS and Conwip. KCS and Conwip were initially invented. More specifically, KCS was the first system developed in the late 70s by Sugimori (González-R et al., 2012).

The developed systems are briefly introduced. First, the original system is described and thereafter its extensions. A detail description of their working mechanism can be found in the associate reference and in the Appendix B.

(1) Kanban Control System (KCS) & Extensions

Kanban Control System (KCS) was the very first PPCS introduced by Sugimori et al., (1977). The principle of KCS is to limit the inventory level of each stage of a process through control loops. Control loops are defined for each workstation in the production line (Gaury, 2000).

(34)

Kiran (1991) etc.). Their difference relates to material handling process between intermediate buffers. In the latter one, two types of cards exist. One is referred to the production (production card). The other one is the transportation card (González-R et al., 2012).

A more versatile system is the Generalized KCS (GKCS) described by Buzacott (1989), Duri et al. (2000a), Duri et al. (2000b), Frein et al. (1995), Karaesmen & Dallery (2000), Koulouriotis et al., (2010). This mechanism is a combination of the rules from KCS (input control works) and Base Stock System (BSS). BSS will be described in a later stage of the paper. Here, base stock level is taken into account. Extended KCS (EKCS), by Dallery & Liberopoulos (2000), Geraghty & Heavey (2005), Karaesmen & Dallery (2000), Koulouriotis et al. (2010), Pedrielli et al. (2015) are similar to GKCS with regard to the combination of KCS and BSS. The difference is the signal transfer of customer demand. The former one transfers instantaneously to all stations, whereas the latter one conveys them in a non-instantaneous process (Dallery & Liberopoulos, 2000). PAC and m-PAC ((modified-) Production Authorization Card control system) introduced by Buzacott & Shanthikumar (1992) use a different type of card to identify orders.

In addition, several Generic models have been proposed for different environmental settings. Those systems are Customized Token Based System 1,2,3,4,5 (CTBS_1,CTBS_2 etc.) by González-r & Framinan, (2009), Gaury´s Generic Model (Gaury´s GM) (Gaury, 2000), Generic KCS by Chang & Yih (1994), Generic Model 1 by Erhun et al. (2003), Generic Model 2, and Generic Model 3 (Gaury, (2000) and Gaury et al., (2001)). In the last system, each stage of a given production line is connected with each preceding stage (Gaury, 2000).

(35)

to a specific product (Gravel & Price, 1988). Chaouiya et al. (2000) differentiate between Simultaneous EKCS (SEKCS) & Independent EKCS (IEKCS). The two systems differ in the way cards are transferred in the workstations of the production line. In the former one, all cards are transferred simultaneously, whereas in the latter one, cards are transferred independently of each other (Chaouiya et al., 2000). Bonvik et al, (1997) combined KCS and Conwip and named it Two-Boundary Hybrid. (here: 2Bound. Hybrid). That system combines the advantages of a KCS (control of inventory at each stage) with those of Conwip system (high TH with low overall WIP). Several other authors (Bonvik & Gershwin (1996), Deleersnydern et al. (1992), Gaury (2000), Geraghty & Heavey (2005), Lavoie et al. (2010)), referred to this system as Hybrid Kanban-Conwip. Hajji et al., (2009) introduced the Hybrid MHCP, which is also a combination of KCS and Conwip but with multiple hedging control points. Hybrid Push/Pull system (Deleersnydern et al., 1992, Ghrayeb et al. (2009) takes into account the demand and the work in progress inventories.

(2) Conwip & Extensions

As noted previously, Conwip (CONstant Work In Process) system have the goal to combine the low inventory levels of Kanban with the high throughput of Push (e.g. Claudio et al. (2010), Claudio & Krishnamurthy (2009), González-r & Framinan (2009), Gstettner & Kuhn (1996)).

(36)

et al. (2011) with the difference of using dedicated cards and local bottleneck at the end of each segment. G-MaxWIP (Grosfeld-Nir & Magazine, 2002) limits WIP as does Conwip by using two different mechanisms (the input rate and the Conwip loop) for controlling the operation of the production line (González-R et al., 2012). CWIPL, as introduced by Sepehri & Nahavandi (2007), improves both throughput (TH) and lead time compared with CONWIP and achieves better results than G-MaxWIP with respect to both TH and lead times in the flow line that has less than nine machines. In addition, CWIPL II was introduced to achieve the same performance, but for unbalanced production line (Nahavandi, 2009). Synchronized Conwip (Takahashi et al., 2005) was developed for unstable environments regarding the arrival rate and processing time. Lödding et al. (2003) introduced DEWIP, with a decentralized control loop between the work centres. M-Conwip uses for each possible routing one control loop, instead of just one control loop for all routings as Conwip does (Germs & Riezebos, 2010). Yang et al. (2011) and Gallien & Wein (2001) proposed M-Closed Conwip, where Conwip cards are dedicated to each product family. In Parallel Conwip (Prakash & Chin, 2011), cards are allocated to two product families. In Conload (Rose (1999) & Rose (2001)), the amount of load for the bottleneck work centre is taken into account. In Reactive Conwip, the buffer size can be controlled in response of unstable demand (Takahashi & Nakamura, 2002).

(3) Base Stock System (BSS) & Extensions

(37)

(4) Cobacabana & Extensions

Cobacabana (Land, (2009), Thürer et al., 2016)) contains two different parts. One is the order release and shop floor control and the another one is responsible for order acceptance and due date promising (Land, (2009)).

(5) Polca & Extensions

POLCA (Paired-cell Overlapping Loops of Cards with Authorization) is referenced by Germs & Riezebos (2010), Krishnamurthy & Suri (2009), Germs & Riezebos (2010), Stevenson et al. (2005) and Thürer et al. (2016). POLCA uses overlapping loops for orders that need to visit more than two workstations (Germs & Riezebos, 2010: 2350). The extended version is called GPOLCA (Fernandes & do Carmo-Silva, 2006). This system implements an input-output control order release strategy on an inventory of production authorization cards instead of materials. In LB-POLCA (Load-Based Polca) (Vandaele et al., 2008) the original unit-based system is changed into the load-based one. Moreover, two cards are assigned to a product: one for the loop that it has just entered, and one for the loop that it is about to leave after processing (Vandaele et al., 2008).

(38)

4.2. Results for the Research Question 2

For the 2nd RQ “What are distinguishing characteristics of these PPCS?”, the results are displayed and commented briefly. First according to configurational aspects and then to structural ones. The graphic 4.1 shows how the selected PPCS from the literature are designed to their configurational aspects. Combinations according to characteristics “Product Anonymous/ Product Specific” and to “Unit Based/ Load Based” are possible. The system names in bolt are the basic/traditional ones. The color shows which extended system and original one belong together. The stripped systems belong to two original systems.

Figure 4.1 Configurational Aspects of PPCS

Obviously, by looking at the graphic 4.1., one can see that a lot of systems have been configured for unit-based characteristics. For the combination load-based and product anonymous, four systems, namely, Conload, LBPolca and GM1 are found. Systems with the combination load-based and product specific were not found.

Load Based

Polca Parallel Conwip reactive Conwip Conload

Gpolca Gated MaxWIP Hybrid MHCP LBPolca

Cobacabana DEWIP 2 Boundary Hybrid GM1

BSS CWIPLII Hybrid Kanban-Conwip Conwip m-Conwip GM2

Conwip Buffer Synch. Conwip GM3 m-Conwip Seg. Conwip Gaury´s GM m-Closed ConwipConwip BSS Generic KCS CWIPL

Dual KCS CTBS_1_2_3_4_5 Generalized KCS Single KCS IKCS PAC

Job-Shop KCS EKCS m-PAC

reactive KCS SEKCS Hybrid Push Pull

Unit Based

PA

(39)

In addition, most PPCS have the configurational aspect of single card. The only exceptions with dual-card are following PPCS: Dual KCS, EKCS, IEKCS, SEKCS, Reactive KCS, and Job-Shop KCS. All dual-card systems are extensions from simple KCS.

Next, the composition of structural aspects of the PPCS is illustrated in the figure 4.2 Since it contains three aspects, a 3D overview with the axis “Decentralized/ Centralized” (x-axis), “Overlapping/ Non-Overlapping” (y-axis) and “Route Specific/ Non-Route Specific” (z-axis) seems to be appropriate to gain a better overview. For example, if we take Single/Dual KCS, the system lies in the field “Decentralized”, “Non-Overlapping”, and “Non-Route Specific”.

Figure 4.2 Structural Aspects of PPCS

(40)

Push/Pull, Generalized GM, reactive KCS, Job-Shop KCS,EKCS, Generic KCS, CTBS1 and m-PAC. The rest (EKCS, 2-Boundary Hybrid, Hybrid Kanban-Conwip, CTBS2, CTBS3, CTBS4, CTBS5, GM2, GM3, Gaury´s GM, SEKCS, IEKCS and Hybrid MHCP) differ in having an “Overlapping” instead of “Non-Overlapping” structural aspect. The only system that differs is the GM1. This one has similar structural aspects as Polca and its extended systems (GPolca, LBPolca) as well as Cobacabana.

In contrast, Conwip is “Centralized”, “Non-Overlapping”, and “Non-Route Specific”. Conwip´s derivatives are almost uniform distributed in three fields: 1) “Centralized”, “Non-Overlapping”, and “Non-Route Specific” (reactive Conwip, Conwip BSS, Parallel Conwip, G-MaxWIP, CONLOAD); 2) “Decentralized”, “Non-Overlapping” and “Non-Route Specific” (M-Closed WIP, Conwip Buffer, and Segmented Conwip), and 3) “Decentralized”, “Overlapping” and “Non-Route Specific” with CWIPL, CWIPL II, Dewip, Synchronized Conwip and m-Conwip.

In areas with the combinations 1) “Decentralized”, “Non-Overlapping”, “Route Specific”, 2) “Centralized”, “Non-Overlapping”, “Route-Specific”, 3) “Centralized”, Overlapping”, “Route Specific”, 4) “Centralized”, “Overlapping”, “Non-Route Specific” are no PPCS at all. However, the combinations 3) and 4) are self-contradictory. Whenever a system has a centralized structure, it cannot have the overlapping aspect at the same time.

(41)

Figure 4.3 Above/Below CL (Gaury 2000)

The control loop linking workstation B and C is below the control loop linking workstations A and D (Gaury, 2000). Several systems from the origin system KCS are found that have that structural aspect: Hybrid (Bonvik & Gershwin (1996), Deleersnydern et al. (1992), Gaury (2000), Geraghty & Heavey (2005), Ghrayeb et al. (2009), Lavoie et al. (2010), 2Boundary Hybrid (Bonvik et al, 1997), Hybrid MHCP (Hajji et al., 2009), CTBS2, CTBS3, CTBS4, CTBS5 (González-r & Framinan, 2009), EKCS (Dallery & Liberopoulos (2000), Geraghty & Heavey (2005), Karaesmen & Dallery (2000), Koulouriotis et al. (2010), Pedrielli et al. (2015)), GKCS (Buzacott , 1989), Duri et al., 2000a), Duri et al. (2000b), Frein et al. (1995), Karaesmen & Dallery (2000), Koulouriotis et al., (2010)).

Gaury´s GM (Gaury, 2000), GM1 (Erhun et al., 2003), GM3 (Gaury, (2000), and IEKCS (Chaouiya et al., (2000). The derivatives of Conwip that have above/below loops are next to the hybrid systems, CWIPL, as introduced by Sepehri & Nahavandi (2007), and CWIPL II (Nahavandi, 2009).

(42)

determine the production sequence in a station. Once a job is finished, the set of priority rules is used to determine which product to produce next (Diaz & Ardalan, 2010). Three different priority rules are found: Shortest Processing Time (SPT), Earliest Due Date (EDD) and First Come First Serve (FCFS). As the names already indicate, with SPT rule, the job with the shortest processing time is selected first and in EDD, jobs are prioritized with the earliest due date (Thürer et al., 2015). FCFS rule is based on the arrival time, where jobs that arrive earlier are given higher priority (Prakash & Chin, 2015). This is suitable for shops where jobs do not have individual due dates (Thürer et al., 2015). Table 4.2. summarizes the priority rules that were used by the selected literature in achieving a desired performance successfully in simulations and experiments. Unfortunately, not all articles indicated the priority rule that was used for the system.

Table 4.2 Structural Aspect: Priority Rules

SPT EDD FCFS

Single/Dual KCS Dewip Conwip

Gpolca Conwip Buffer

Polca EKCS GKCS M-Closed Conwip CONLOAD GM1 GM2 CWIPL CWIPL II Single KCS Dual KCS Seg. Conwip 2 Bound. Hybrid Cobacabana

(43)

Figure 4.4 Updated Conceptual Model

4.3.Results for the Research Question 3

Now, the last, the 3rd RQ “Which PPCS are most effective in which environmental conditions?” is answered. First, figure 4.5 gives an overview of PPCS that are assigned to be most suitable according to the organizational typology (PFS/GFS & PJS/GJS) in the x-axis and to the organizational strategy (MTO/MTS) in the y-axis:

(44)

In accordance to this illustration, it can be noted that most systems are suitable for MTS/PFS field. These systems are the original single/dual KCS and its derivatives Hybrid MHCP, CTBS2, CTBS3, CTBS4, CTBS5, Generalized KCS, 2 Boundary Hybrid, Hybrid Kanban-Conwip, Hybrid Push Pull, GM2, GM3 and reactive KCS. In the same field are Conwip with its derivatives from G-MaxWIP, Parallel Conwip, Conwip BSS, Segmented Conwip, Synchronized Conwip, CWIPL, M-Closed WIP, Conwip Buffer, and reactive Conwip.

Gaury´s GM and CONLOAD were not specified in particular besides of the fact that they work well in flowshops in MTS. GM1 is suitable for MTS/GFS. Systems like CWIPL II, PAC and m-PAC are suitable for MTO/MTS and PFS combination.

For the combination MTO/PFS M-Conwip, as the only derivative from Conwip is suitable. In addition, CTBS1, EKCS, IEKCS, SEKCS and GKCS fit also in the same field as derivatives from KCS.

Polca and GPolca are the only two systems for the combination MTO/GFS. However, for jobshop just a few systems work. Cobacabana is suitable for jobshops with MTO strategy. For the combination MTO/GJS, which is the most extreme but flexible environment, LBPolca, DEWIP, and Job-Shop KCS can be applied.

In addition, hybrid push/pull system with constant arrival and processing times, no set-up times, no routing, no product mix are suitable for ATO manufacturing environment.

(45)

No. The light grey path represents the original systems. The dark ones represent the extended ones. Next to the system, a small box indicates what performance is possible to achieve.

(46)

Figure 4.7 PPCS in MTS & GFS

(47)

Figure 4.9 PPCS in MTO& GFS; in MTO & PJS; in MTO & GJS

4.4. The Unified Framework

This chapter provides an overview of how to customize PPCS, if the organization is confronted with specific environmental circumstances in order to safeguard performance. Figures 4.10 illustrates the actual unifying framework.

To be able to draw the framework, summing up the found characteristic of PPCS that achieve a certain degree of performance in the described environment would lead to false conclusions. Therefore, conducted comparative studies from retrieved literature were taken for designing the framework. PPCS without any comparison were excluded. The excluded PPCS are listed in the “limitation”.

(48)

product mix”, the configurational aspect “Product Specific” must be changed from “Product Anonymous” to realize a certain performance. On the other side, for environments with “random processing time”, the structural aspects “Decentralized” and “Overlapping” replace their counterparts. If the system operates close to capacity, “Above/Below Loops” should be implemented to realize low WIP and SL when arrival time is constant or random and whenever processing times are random. In addition, the sequencing rules show which rule is recommended for which environment. However, due to still explorative field, the picture of priority rules is incomplete.

To sum up, the more complex environmental settings are, the more complex the designing and managing PPCS gets.

(49)

5. Discussion

The main goal of this study is to show which PPCS have been developed, what are their distinguishing characteristics and how they fit to certain environmental settings. Based on the selected literature, a final unified framework of designing PPCS is generated. However, several points need more attention and should be discussed.

5.1.Customized PPCS and Above/Below Loop

One of the study's most conspicuous findings include the fact that the different versions of Hybrid systems (Hybrid, 2Boundary Hybrid, Hybrid MHCP) as well as customized ones (e.g. CTBS2, CTBS3, CTBS4 etc.) have the design characteristic of “Above/Below Loop”. Gaury et al. (2001) claim in their research that each production system has its own specifications. Therefore, predefined systems like KCS and Conwip might not be sufficient. Instead customized/ hybrid systems are needed (Gaury et al., 2001). For this, an individual investigation of the system and experiments are needed to draw conclusions where and how many below loops (Kanban loops) and above loops (Conwip loops) should be located. For example, in case of the Hybrid systems in Gaury et al. (2000), all three different versions of Hybrid achieved the best performance of WIP, when the inventory allocation along the line is balanced in the middle, slightly higher at the beginning, and high at the end (Gaury et al., 2000).

(50)

5.2. Sequence of Cards

The literature contains contradicting opinions whether the sequence of cards influence the actual performance of the system. Yang (2000) showed through his simulation that priority rules have a smaller impact on the TTT and total WIP than other policy variable like the number of cards. Just recently, Thürer et al. (2015) found an explanation, why the sequence rule FCFS was applied for the majority of experiments: First of all, when card-based systems have been developed, there were no (or little) processing time variability. Consequently, priority rules like shortest processing time (SPT) were insignificant. In addition, the original systems were intended to work in a MTO environment. Here, jobs have no individual due dates. Again, FCFS seemed to be reasonable to apply (Thürer et al.,2015).

Nevertheless, some papers concluded that the selected sequencing method affects the performance of the system (Lummus, 1995) and compared the found rules (Berkley & Kiran, 1991, Berkley, 1993 and Huang & Kusiak, 1996). The unified framework contains the results from comparative studies. Unfortunately, for some environmental circumstances, as for constant/ random arrival time, route variability, set-up time and product mix a clear direction from the literature is missing.

5.3. Designing of PPCS for different Environments

Great number of papers compared the performance of different PPCS under the same environmental circumstances and drew conclusions which system achieves better performance. The results of those comparisons build the ground for designing the framework.

(51)

about Conwip that the system can accommodate both small and infrequent orders as well as changing product mix and thus outperforms simple KCS. This study was conducted under constant arrival and processing times. Some time later, Conload was introduced by Rose (1999) and Rose (2001). In his researches, the author concluded that Conload allows quicker reaction on product mix changes than Conwip. Few years later, Bonvik et al., (1997) made a comparison between the three PPCS KCS, Conwip and 2 Boundary Hybrid which resulted in the fact, that the hybrid policy outperforms the other policies in terms of WIP and SL in more complex environments. A more recent comparison made by Germs & Riezebos (2010) compared Conwip to more complex systems (m-Conwip and Polca). They conclude that m-Conwip and Polca outperform the simple model in terms of TH in complex environment that included routing variability. These studies are very valuable and give clear guidance for choosing certain design aspect to achieve a desired performance.

However, for a lot of systems that are suitable for the same environmental circumstances and pursuit the same type of performance, a cross-case comparison is missing in the literature and cannot be made out of the literature review. For example, for environments with product mix, PAC, m-PAC (Buzacott & Shanthikumar, 1992), and Conload (Rose, 1999 and 2001) are suitable to safeguard a certain level of WIP, even though they differ in their design characteristics.

5.4. Implications for Practitioners

(52)

thesis, practitioners can see that PPCS are not restricted to simple systems like KCS and Conwip only, rather the literature offers a great number of variety. What is more, the results of the second research question provide insights of how PPCS differ in their design characteristics. The outcome of the third research question illustrates a decision tree of which PPCS is most effective in which environmental condition. Here, the practitioners can first select the strategy and typology that they need for their manufacturing. Next, the different path through the environmental conditions guide the reader to a PPCS that was used successfully in the literature.

But the most important result presents the actual unified framework. Thanks to this framework, the practitioners can design their own PPCS that is suitable for their environment while safeguarding performance. What is more, this framework shows which design elements increase complexity. Consequently, whenever possible, managers can decide if the implementation of increasing complexity is necessary. All in all, as initially promised, practitioner can select or even customize their own system.

5.5.Implications for Academics

An additional goal of the research was to show academics to what extent the research developed and analyzed PPCS, and thereby detect possible gaps in the literature. The results of the first research question demonstrate what PPCS have been developed. Moreover, the PPCS are classified into the original and extended systems, whereas the extended are visible classified to their original derivatives. In the next step, the found PPCS are classified according to their structural and configurational aspects.

(53)

shows, that PPCS with the aspects “Unit Based”, “Product Anonymous”, and “Product Specific” were extensive assessed. On the other side, only three systems with the design combination “Load Based” & “Product Anonymous” were found, whereas no systems exist “Load Based” & “Product Specific”. The overview with structural aspects shows where research has been focused in the past and how developed PPCS are designed. Since design combinations “Centralized”, “Overlapping”, “Route Specific”, and “Centralized”, “Overlapping”, “Non-Route Specific” are self-contradictory, research on design aspects combinations with 1) “Decentralized”, “Non-Overlapping”, “Route Specific”, and 2) “Centralized”, “Non-“Non-Overlapping”, “Route-Specific” could focus. These combinations are gaps in the literature.

What is more, the figure of PPCS that are assigned to the organizational typology and strategy does also indicate where gaps in the literature exist. Namely, PPCS for more complex environments. In addition, sequencing rules in more complex environments should be compared to be able to give clear directions and round up the framework. But most importantly, academics should more focus on comparing the performance of counterpart design elements under the same experimental conditions, which might even result in a deviation of the developed framework.

5.6.Limitations & Future Research

Even though a unified framework was developed to give a general guideline to select the most appropriate design elements for the given circumstances, there are some limitations that have to be taken into account.

(54)

2011), Hybrid MHCP (Hajji et al., 2009), Reactive KCS (Takahashi & Nakamura, 2002) and Job-shop KCS (Gravel & Price, 1988). Future research should make a proper performance comparison with other systems in order to see if those named complex system help to achieve better performance.

What is more, this paper focused on environmental factors and not the design of the production line. This can also influence the choice on the design of PPCS. Research studies in Gaury (2000) and Gaury et al. (2001) considered the line length, line imbalance, imbalance pattern etc. Koulouriotis et al. (2010) achieved in their simulation study different performance results for assembly and serial lines.

(55)

6. Conclusion

In conclusion, the answer for the first research question (“What PPCS have been developed?”), which is illustrated in table 4.1., gives a good overview. Five basic/ original systems have been found with a large number of their derivatives. This holds particular true from Single/Dual KCS and Conwip as those ones are the oldest systems that have been developed. The references for each PPCS can be used for deeper insights of each system. This paper describes very briefly the working principle for each of 43 found systems.

For the second RQ (“What are distinguishing characteristics of these PPCS?”), the configurational and structural characteristics of each systems were first deconstructed. This step enabled to provide an overview of where or with what design aspects the most systems were developed in the past. Figure 4.1. summarizes the configurational aspects of PPCS. It is apparent, that most systems have the combination “unit-based” and “product specific”. The deductive coding also resulted in a dominant design aspect regarding structural aspects illustrated in figure 4.2. KCS and its derivatives are distributed in the field of “Decentralized”, “(Non-)Overlapping”, and “Non-Route Specific”. More movements can be noticed from Conwip and its derivatives. The recent developed systems as Cobacabana and Polca dominate the field of the design aspects “Decentralized”, “Overlapping”, and “Route Specific”. Moreover, through inductive coding, a new design element is added: Above/Below Loop and a new variable that influence performance of the system, namely sequence of cards, was added. Therefore, an updated conceptual model is drawn and used for the rest of the research.

(56)

framework visualizes for which environmental setting, which configuration and design aspect is most appropriate to safeguard certain level of performance. It enables customization of an own system.

(57)

References

Akturk, M. S., & Erhun, F. (1999). An overview of design and operational issues of kanban systems. International Journal of Production Research, 37(17), 3859–3881.

Ardalan, A. (1997). Analysis of local decision rules in a dual-kanban flow shop. Decision Sciences, 28(1), 195–211.

Ardalan, A., & Diaz, R. (2012). An evaluation of the NERJIT priority rule in a kanban-controlled flowshop. Production and Operations Management, 21(5), 923–938. Ardalan, A., & Diaz, R. (2012). NERJIT: Using net requirement data in kanban-controlled

jumbled-flow shops. Production and Operations Management, 21(3), 606–618. Berkley, B. J. (1993). Simulation Tests of FCFS and SPT Sequencing in Kanban Systems.

Decision Sciences, 24(1), 218–227.

Berkley, B. J., & Kiran, A. S. (1991). A Simulation Study of Sequencing Rules in a Kanban-Controlled Flow Shop. Decision Sciences, 22(3), 559–582.

Berkley, J. (1992). A review of the KANBAN production control research literature. Production and Operations Management, 1(4), 393–411.

Bonvik, A. M., Couch, C. E., & Gershwin, S. B. (1997). A comparison of production-line control mechanisms. International Journal of Production Research, 35(3), 789–804.

Bonvik, A. M., & Gershwin, S. B. (1996). Beyond kanban – creating and analyzing lean shop floor control policies. Proceedings of Manufacturing and Service Operations Mangagement Conference.

(58)

Buzacott, J. A. (1989). Queueing models of Kanban and MRP controlled production systems. Engineering Costs and Production Economics, 17(1–4), 3–20.

Buzacott, J. A., & Shanthikumar, J. G. (1992). A General Approach For Coordinating Production In Multiple-Cell Manufacturing Systems. Production and Operations Management, 1(1), 34–52.

Chang, T. M., & Yih, Y. (1994). Generic Kanban systems for dynamic environments. International Journal of Production Research, (32), 889–902.

Chaouiya, C., Liberopoulos, G., & Dallery, Y. (2000). The extended kanban control system for production coordination of assembly manufacturing systems. IIE Transactions, 32(10), 999–1012; 1012.

Cigolini, R., Perona, M., & Portioli, A. (1998). Comparison of Order Review and Release techniques in a dynamic and uncertain job shop environment. International Journal of Production Research, 36(11), 2931–2951.

Claudio, D., & Krishnamurthy, A. (2009). Kanban-based pull systems with advance demand information. International Journal of Production Research, 47(12), 3139–3160.

Claudio, D., Zhang, J., & Zhang, Y. (2010). A simulation study for a hybrid inventory control strategy with advance demand information. International Journal of Industrial and Systems Engineering, 5(1), 1–19.

Dallery, Y., & Liberopoulos, G. (2000). Extended kanban control system: Combining kanban and base stock. IIE Transactions (Institute of Industrial Engineers), 32(4), 369–386. Deleersnydern, J.-L., Hodgson, T. J., King, R. E., O´Grady, P. J., & Savva, A. (1992).

(59)

Diaz, R., & Ardalan, A. (2010). An analysis of dual-kanban just-in-time systems in a non-repetitive environment. Production and Operations Management, 19(2), 233–245. Duri, C., Frein, Y., & Di Mascolo, M. (2000). Comparison among three pull control policies:

Kanban, base stock, and Generalized Kanban. Annals of Operations Research, 93(1), 41–69. Duri, C., Frein, Y., & Lee, H.-S. (2000). Performance evaluation and design of a CONWIP

system withinspections. International Journal of Production Economics, 64(1–3), 219–229. Erhun, F., Akturk, M. S., & Turkcan, A. (2003). Interaction of design and operational parameters in periodic review kanban systems. International Journal of Production Research, 41(14), 3315–3338.

Fernandes, N. O., & do Carmo-Silva, S. (2006). Generic POLCA-A production and materials flow control mechanism for quick response manufacturing. International Journal of Production Economics, 104(1), 74–84.

Framinan, J. M., González, P. L., & Ruiz-Usano, R. (2003). The CONWIP production control system: Review and research issues. Production Planning & Control, 14(3), 255–265. Fredendall, L. D., Ojha, D., & Wayne Patterson, J. (2010). Concerning the theory of workload

control. European Journal of Operational Research, 201(1), 99–111.

Frein, Y., Di Mascolo, M., & Dallery, Y. (1995). On the Design of Reliable Control Systems. International Journal of Operations & Production Management, 15(9), 158–184.

Gallien, J., & Wein, L. M. (2001). A simple and effective component procurement policy for stochastic assembly systems. Queueing Systems, 38(2), 221–248.

Gaury, E. G. A. (2000). Designing pull production control systems: Customization and robustness. Tilburg University.

(60)

Control Systems. The Journal of the Operational Research Society, 52(7), 789–799.

Gaury, E. G. A., Pierreval, H., & Kleijnen, J. P. C. (2000). Evolutionary approach to select a pull system among Kanban, Conwip and Hybrid. Journal of Intelligent Manufacturing, 11(2), 157–167.

Geraghty, J., & Heavey, C. (2005). A review and comparison of hybrid and pull-type production control strategies. OR Spectrum, 27(2–3), 435–457.

Germs, R., & Riezebos, J. (2010). Workload balancing capability of pull systems in MTO production. International Journal of Production Research, 48(8), 2345–2360.

Ghrayeb, O., Phojanamongkolkij, N., & Tan, B. A. (2009). A hybrid push/pull system in

assemble-to-order manufacturing environment. Journal of Intelligent Manufacturing, 20(4), 379–387.

González-r, P. L., & Framinan, J. M. (2009). The pull evolution : from Kanban to customised token-based systems. Production Planning & Control, 20(3), 276–287.

González-R, P. L., Framinan, J. M., & Pierreval, H. (2012). Token-based pull production control systems: An introductory overview. Journal of Intelligent Manufacturing, 23(1), 5–22. Gravel, M., & Price, W. L. (1988). Using the Kanban in a job shop environment. International

Journal of Production Research, 26(6), 1105–1118.

Grosfeld-Nir, A., & Magazine, M. (2002). Gated MaxWIP: A strategy for controlling multistage production systems. International Journal of Production Research, 40(11), 2557–2567. Gstettner, S., & Kuhn, H. (1996). Analysis of production control systems kanban and CONWIP.

International Journal of Production Research, 34(11), 3253–3273.

(61)

352.

Gurgur, C. Z., & Altiok, T. (2007). Analysis of decentralized multi-product pull systems with lost sales. Naval Research Logistics (NRL), 54(4), 541–550.

Hajji, A., Gharbi, A., & Kenne, J. P. (2009). Production and changeover control policies of failure prone buffered flow-shops. Production Planning & Control, 20(8), 785–800. Hopp, W. J., & Spearman, M. L. (2001). Factory Physics Principles. Cycle. Boston: Irwin/

McGraw-Hill.

Hopp, W. J., & Spearman, M. L. (2004). To Pull or Not to Pull: What Is the Question? Manufacturing & Service Operations Management, 6(2), 133–148.

Huang, C.-C., & Kusiak, A. (1996). Overview of Kanban systems. International Journal of Computer Integrated Manufacturing, 9(3), 169–189.

Huang, P. Y., Rees, L. P., & Taylor, B. W. (1983). A simulation analysis of the Japanese just-in-time technique (with kanbans) for a multiline, multistage production system. Decision Sciences, 14(3), 326–344.

Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171(1), 116–133.

Karaesmen, F., & Dallery, Y. (2000). A performance comparison of pull type control

mechanisms for multi-stage manufacturing. Int. J. Production Economics, 68(1), 59–71. Khojasteh, Y. (2016). Production Control Systems: a guide to enhance performance of pull

systems. Tokyo, Japan: Springer.

(62)

Koulouriotis, D. E., Xanthopoulos, A. S., & Tourassis, V. D. (2010). Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms. International Journal of Production Research, 48(10), 2887–2912. Krajewski, L. J., King, B. E., Ritzman, L. P., & Wong, D. S. (1987). Kanban, MRP, and Shaping

the Manufacturing Environment. Management Science, 33(1), 39–57.

Krishnamurthy, A., & Suri, R. (2009). Planning and implementing POLCA: a card-based control system for high variety or custom engineered products. Production Planning & Control, 20(7), 596–610.

Krishnamurthy, A., Suri, R., & Vernon, M. (2004). Re-examining the performance of MRP and kanban material control strategies for multi-product flexible manufacturing systems. International Journal of Flexible Manufacturing Systems, 16(2), 123–150.

Lage Junior, M., & Godinho Filho, M. (2010). Variations of the kanban system: Literature review and classification. International Journal of Production Economics, 125(1), 13–21. Land, M. J. (2009). Cobacabana (control of balance by card-based navigation): A card-based

system for job shop control. International Journal of Production Economics, 117(1), 97– 103.

Land, M. J., & Gaalman, G. J. C. (1998). The performance of workload control concepts in job shops: Improving the release method. International Journal of Production Economics, 56– 57, 347–364.

Lavoie, P., Gharbi, A., & Kenné, J. P. (2010). A comparative study of pull control mechanisms for unreliable homogenous transfer lines. International Journal of Production Economics, 124(1), 241–251.

University of Groningen