Lauri Krats
Application-based to platform-based systems in product engineering
Metropolia University of Applied Sciences Bachelor of Engineering
Industrial Management Bachelor’s Thesis 1 June 2021
Author Title
Number of Pages Date
Lauri Krats
Application-based to platform-based systems in product engi- neering
41 pages 1 June 2021
Degree Bachelor of Engineering
Degree Programme Industrial Management Professional Major Process Management
Instructors Panu Rahikka, Head of Engineering GBL Finland Juha Haimala, D.Sc. (Tech), Principal Lecturer
The objective of this thesis was to develop a model for assessing readiness for transfor- mation to platform-based approach with product development and product engineering IT systems. Smart connected products and the new competitive field has forced manufacturing companies to re-assess the applicability of the existing systems, and Product Lifecycle Man- agement system has become a core business system of a manufacturing company. This thesis explores what are the factors affecting the transformation potential from the applica- tion-based systems towards the platform-based approach.
The thesis was conducted by using a design research approach, which aims to understand a phenomenon and solve a problem. At first, extensive number of interviews were held, using qualitative research methods to understand the current state of the product develop- ment and engineering IT systems within the Finnish manufacturing industry. In parallel with the current state analysis, literature best practice of product development and engineering systems, product lifecycle management, and digital transformation potential were reviewed.
The key findings from the current state analysis as well as the literature review was brought for discussion with the case company, to associate the findings with the existing knowledge.
The development phase of the model was carried out based on the combination of these elements.
The transition model was developed to address the thesis objective. The model integrates the enterprise maturity assessments considering organizations product development and engineering aspects as well as the transition model attributes built based on the findings of the current state analysis and the literature review. The transition model includes a portfolio- focus view, categorizing the companies on three stages, which are concept, build, and ex- pand. The journey towards the platform-based approach starts from the concept-stage, by building a digital strategy and roadmap. Lastly, the expand-stage include an organization wide adoption of platform-based solutions, contributing to end-to-end digital continuity.
Keywords Product development, product engineering, product lifecycle management, transformation
Tekijä Otsikko Sivumäärä Aika
Lauri Krats
Muutos sovelluspohjaisista tuotekehitysjärjestelmistä kohti alustapohjaisia ratkaisuja
41 sivua 1.6.2021
Tutkinto Insinööri (AMK)
Tutkinto-ohjelma Tuotantotalous
Ammatillinen pääaine Teollisuuden Prosessit
Ohjaajat Panu Rahikka, Head of Engineering GBL Finland Juha Haimala, TkT, Yliopettaja
Tämän insinöörityön tavoite oli esittää malli muutosvalmiuden arvioimiseksi sovelluspohjaisista tuotekehitysjärjestelmistä kohti alustapohjaisia järjestelmiä. Älykkäät ja ekosysteemeihin liitettävät teolliset tuotteet sekä nykyaikainen kilpailukenttä ovat osaltaan pakottaneet valmistavan teollisuuden yritykset arvioimaan kriittisesti nykyisten tuotekehitysjärjestelmien soveltuvuutta, ja tuotteen elinkaaren hallintajärjestelmästä on tullut yksi valmistavan teollisuuden yritysten ydinjärjestelmistä. Tämä insinöörityö tutkii, mitkä ovat vaikuttavia tekijöitä muutosvalmiutta sovelluspohjaisista järjestelmistä kohti alustapohjaisia arvioitaessa.
Insinöörityö toteutettiin sovellettuna toimintatutkimuksena, joka pyrkii ymmärtämään ilmiötä sekä ratkaisemaan ongelman. Ensiksi kattava määrä haastatteluja toteutettiin käyttämällä laadullisia tutkimusmenetelmiä, tarkoituksena rakentaa nykytila-analyysi tuotekehitysjärjestelmien tilasta suomalaisten valmistavan teollisuuden yritysten keskuudessa. Samanaikaisesti aloitettiin kirjallisuustutkimus, tarkoituksena tunnistaa parhaat käytännöt tuotekehitysjärjestelmistä, tuotteen elinkaaren hallinnasta, sekä muutosvalmiudesta. Merkittävimmät löydökset sekä nykytila-analyysista että kirjallisuustutkielmasta esiteltiin insinöörityön kohdeyritykselle, tarkoituksena yhdistää löydöksiä kohdeyrityksen asiantuntijoiden kokemusperäisen tiedon kanssa, luoden perusta työn tulosten kehittämisvaiheelle.
Työn tuloksina kehiteltiin malli vastaamaan työlle asetettua tavoitetta. Malli yhdistää organisaation kypsyyden arvioinnin tuotekehitysjärjestelmien suhteen sekä mallia varten rakennetut attribuutit, jotka pohjautuvat nykytila-analyysin sekä kirjallisuustutkielman löydöksiin. Muutosvalmiutta arvioiva malli sisältää myös kohdeyrityksen palveluportfolio- näkökulman, joka tunnistaa kolme kategoriaa: konseptointi, rakennus, ja laajennus. Mallin mukainen muutos kohti alustapohjaisia järjestelmiä alkaa konseptointi-vaiheesta, jossa määritellään strategia ja tiekartta muutokselle. Laajennus-vaihe lopulta käsittää alustapohjaisten ratkaisujen koko organisaation laajuisen käyttöönoton, mahdollistaen digitaalisen jatkuvuuden.
Avainsanat Tuotekehitys, tuotteen elinkaaren hallinta, transformaatio
Contents
List of Abbreviations
1 Introduction 1
1.1 Business Context 1
1.2 Business Challenge, Objective and Outcome 2
2 Project Plan 3
2.1 Research Design and Timeline 4
2.2 Data Collection and Analysis 7
3 Current State Analysis 9
3.1 Approach and Scope 9
3.2 Findings from the Manufacturing Industry 11
3.3 Summary of the Key Findings 12
4 Best Practice of Platform-based Product Engineering Solutions 14
4.1 Product Development and Engineering 17
4.2 Product Lifecycle Management 21
4.3 Enterprise Maturity Model 23
4.4 Transformation Potential 26
5 Transition to Platform-based Solutions 29
5.1 Development Work 29
5.1.1 Business and Organization 30
5.1.2 System Scope and Infra 31
5.1.3 Product 32
5.1.4 Industry 32
5.2 Transition Model Proposal 33
6 Final Proposal 37
7 Conclusions 40
7.1 Assessment of the Work 40
7.2 Reliability and Validity 41
References 42
List of Abbreviations
BOL Beginning of Life
CAD Computer Aided Design CAE Computer Aided Engineering CAM Computer Aided Manufacturing CNC Computer Numerical Control
CRM Customer Relationship Management CSA Current State Analysis
EOL End of Life
ERP Enterprise Resource Planning ETO Engineer to Order
GBL Global Business Line IT Information Technology MOL Middle of Life
MU Market Unit
OT Operational Technology OS Operating System
PDM Product Data Management
PLM Product Lifecycle Management R&D Research & Development
SIAM Service Integration and Management
1 Introduction
This thesis explores product development and product engineering Information Technol- ogy (IT) systems, and transition from application-based to platform-based approach.
Product development can be viewed as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale (Zhang et al. 2019: 6-7). Along with this definition, product development refers to developing a new product, whereas in the context of this thesis, product engineering means processes and actions for engineering a product to fulfill customer order. These products can be referred to as engineer-to-order (ETO) products, and these processes commonly include substantial amount of design and engineering analysis operations. Particularly this thesis focuses on engineering IT systems of industrial manufacturing companies operating in the Finnish market.
1.1 Business Context
The case company of this thesis is an IT and Engineering service provider and a global leader in consulting, digital transformation, technology, and engineering services. This thesis is conducted for the case company’s Market Unit (MU) Finland, in co-operation with Engineering Global Business Line (GBL). Within MU Finland, Engineering business is relatively new, and actively taking foot place in the Finnish market.
Engineering GBL offers solutions and services to varying industries, for stakeholders from design, engineering, manufacturing, operations, and after-sales. The offering port- folio includes complete solutions for product lifecycle management (PLM), a business system with growing potential and popularity among manufacturing companies. Radha- krishnan (2008: 36) describes that PLM software views the entire lifecycle of a product as a process, which can be managed, measured, monitored, and modified to achieve continuous improvement.
Application-based approach on product development represents a bottom-up approach on a system perspective, based on integrated systems through coordination of functional entities. Practically this means that the IT system scope is a composition of many indi- vidual software, implemented to meet the needs of a certain function. It is common that there are many different IT system vendors and the development of these systems is not streamlined. Each software performs the key tasks for which it was implemented for, and integrations are built for interoperability.
Platform-based approach represents a top-down approach on a system perspective and initiates by considering the business needs of an organization. Smart services are one modern representation of these business needs. Platform-based approach on product development and engineering IT systems can be achieved by IT transformation, and PLM software is the backbone for that among manufacturing companies. The product and its specifications are strongly connected to system requirements and is a factor of the business potential of potential customers.
1.2 Business Challenge, Objective and Outcome
The case company aims to grow Engineering business in Finland by leveraging strong group capabilities as well as gradually expanding local capabilities. The goal is to achieve growth by establishing new strong partnerships with Finnish manufacturing companies.
The business challenge for the case company is to understand the current state of po- tential customer companies as well as future direction and plans, what are the necessi- ties for potential customer’s business. By these means the case company can better understand how to improve and develop solutions and services and how to be a relevant choice for potential customers.
The objective of this thesis is to propose a model for assessing readiness for transfor- mation to platform-based approach. This is done by identifying company characteristics that make them ready for transformation. Assessment of the business potential of cus- tomer company for Engineering business can be derived from the model. The outcome of this thesis is a transformation readiness assessment model, which includes themes discovered by integrating Current State Analysis (CSA) findings with existing knowledge obtained by the literature review.
2 Project Plan
This thesis is conducted as design research, which Kananen (2013: 12) describes as a bridge between the worlds of theory and empiria, to understand a phenomenon or to solve a problem. Furthermore, he describes that in the background of design research is a situation that one wants to be improved after development or change. Design re- search is close to development work that is being conducted in organizations to improve operations. It is not its own methodology of research, but a group of different methodol- ogies that are being used according to a situation or an objective of development. As a process design research has characteristics of action and development research (Ka- nanen 2013: 12-14).
According to Kananen (2013: 40-44) action research aims for a change or development of a thing and becomes action research through the fact that the practitioner is testing the functionality of the solution themselves. The difference between design and action research is diminutive when considering how the research itself is done, but quite clear considering that in action research the practitioner is participating in the operations of the development object and action, research, and change are realized at the same time, whereas in design research, the practitioners participation in the operations of a devel- opment object is not required. Design research is not satisfied only describing, under- standing, or explaining states of affairs or phenomenon, but aims to discover better op- tions and alternatives (Kananen 2013: 50-51).
Design research includes two processes, targeted development work and research which results in a thesis. The research process follows methodologies applicable de- pending on the subject to development. The development work progresses in cycles, commonly with one development cycle following another, as Figure 1 visualizes (Ka- nanen 2013: 59-61).
Figure 1. Development work cycle (Kananen 2013: 61).
Design research approach is selected for the thesis work due to its applicability for busi- ness challenge development in a variety of contexts, and its empirical nature. The fol- lowing sub-chapter describes in more detailed and practical level, how the thesis work is conducted, following with the data collection and analysis plan.
2.1 Research Design and Timeline
The thesis project initiates from co-operative actions of the author, MU Finland Engineer- ing business head and sales manager, by defining the business challenge and objective.
This is followed by obtaining an approval for the thesis title from Metropolia and docu- menting the project plan for the thesis. To conduct the project plan, the needed work units and activities is mapped and evaluated against research objective. Identified activ- ities is sequenced, including the prospective work units. Figure 2 presents the research design for the thesis.
Figure 2. Research design
1. OBJECTIVE Propose a model for assessing readiness for
transformation to platform-based systems
2. CURRENT STATE ANALYSIS Analysis on the current situation of the PE systems
and operations among manufacturing industry DATA 1
9 potential customer company interviews
2 industry expert interviews W43-2020 – W05-2021
OUTCOME Market outlook, strengths, and weaknesses
3. LITERATURE REVIEW Smart Connected Products Product Development and
Engineering systems Digital Transformation
OUTCOME Conceptual framework
4. PROPOSAL BUILDING Development work for associating CSA findings with
literature review
OUTCOME Maturity assessments
Transition model
5. VALIDATION OF PROPOSAL Evaluation of initial proposal
against objective
OUTCOME Validated final proposal DATA 2
Interview: Program Manager Mechanical Design & Simulation
February 4th, 2021
DATA 3 Interview: MU Finland Engineering business Head
March 24th, 2021 Interview: Sales Manager
March 31st, 2021
As seen in Figure 2, the Data 1 collection by qualitative method is the first activity after objective setting, with an objective to create a current state analysis on product develop- ment and engineering operations from IT system perspective. This is conducted by qual- itative interviews, organized with industrial manufacturing companies operating in the Finnish market. The focus is to identify the characteristics of the products, what is ex- pected from IT systems in their domain, to map out the current product engineering IT system scope and to identify strengths and weaknesses as well as potential success cases. Outcome of this phase is the key factors for transformation potential assessment for later association with literature findings.
In parallel with qualitative research, the literature review is initiated to have an approach on identified product engineering solutions and to review the literature best practices on platform-based approach, as well as favorable configurations for product development and engineering. The objective is to create a conceptual framework to understand and assess the transformation readiness and potential, and the focus is on identifying, what are the key enablers, barriers, and business benefits of implementing the top-down, plat- form-based approach.
The following phase is practical research, for associating the current state analysis find- ings with literature best practices. The purpose is to understand, how to evaluate the maturity of the companies in the Data 1 collection scope and assess the possibilities for transition to top-down, platform-based approach. This is conducted by internal interviews with the case company’s experts from Engineering GBL. The objective is to create a maturity model for the companies in the Data 1 collection scope, and a transition model as an initial proposal for results.
In the final phase, the initial proposal is evaluated against business challenge and ob- jective of the thesis, by collecting feedback from relevant stakeholders. The solution pro- posal is reviewed by the case company side as well as Metropolia, and corrective ad- justments made and concluded in the outcomes and results of the thesis. Finally, the conducted work is assessed against objective and summarized for thesis closure.
2.2 Data Collection and Analysis
The purpose of this data collection plan is to provide a framework on how and what data is collected and how it is utilized in the thesis project. This plan also aims to help with understanding how to prevent collecting non-relevant data, which will not be utilized dur- ing the project. Table 1 presents the data collection plan.
Table 1. Data collection plan
Content Source Planned outcome
Data 1 Current State Analysis
Identification of charac- teristics, operations, and processes
Used applications and systems
Strengths and weak- nesses, similarities
Interviews with 9 potential customer companies from different industries and 2 in- dustry expert interviews W43-2020 – W05-2021
Respondent’s from IT, R&D, and business functions
CSA
Outlook on company’s cur- rent state with product, prod- uct engineering operations and related IT systems
Analysis of maturity, strengths, weaknesses, and similarities
Data 2 Building the pro- posal
How to associate CSA findings with literature review and conceptual model design
How to evaluate maturity and transformation readi- ness
Interview: Program Manager Mechanical Design & Simula- tion
February 4th, 2021
Maturity model Transition model Initial proposal
Data 3 Validation
Evaluation of initial pro- posal against objective
Interview: MU Finland Engineering business Head March 24th, 2021
Interview: Sales Manager, March 31st, 2021
Final proposal
The development work of final proposal is based on qualitative data collection, literature review and practical research. These can also be interpreted by identifying two initial phases: current state analysis on product engineering operations of industrial companies from IT system perspective (Data 1 collection) and theory research on product engineer- ing solutions and enablers for transformation to platform-based approach. Continuing with two supporting phases: practical research to understand how to associate current state analysis findings with literature review (Data 2 collection) and feedback from initial proposal of maturity and transition models.
Table 2. Data analysis plan
Steps in analysis
planning Content
Purpose Current state analysis, strengths and weaknesses, best prac- tices, known solutions
Data available Gathered information, written practices and other literature, professional knowledge
Amount of data needed
Core data to understand current state, data to understand business benefits of solutions and barriers for implementation
Measuring of data Inductive content analysis from interview answer and litera- ture findings
Collector of data The author
Source of data Collection of Data 1 & Data 2, literature from e-book data- bases available, internal documentation of the case company
Sampling method Qualitative measurement on the population of collected data
Display of data Visualizations into charts, tables, and models
As Table 2 presents, the data analysis plan helps to understand how gathered data is processed and utilized during the thesis project. The data analysis plan aims to help meeting the objective of the thesis and provide logical tools and guidance for the author.
3 Current State Analysis
This chapter provides an outlook on the product development and engineering IT sys- tems and operations of industrial manufacturing companies, operating in the Finnish market. The current state analysis relies on the Data 1 collection, by interviews on com- panies from very different industries and size to gain a broad perspective on what is expected from the product development and engineering systems, what are the known key challenges, and to identify success cases. These findings will be used to associate them with the best practice of platform-based product engineering systems as well as other literature findings, to understand and assess, by what means a company can make a transition towards a platform-based approach on their product development and engi- neering systems.
3.1 Approach and Scope
The approach for conducting the current state analysis is by qualitative method. The purpose of qualitative research approach is gaining more in-depth understanding of a phenomenon. To conduct the current state analysis, the scope of industrial manufactur- ing companies is identified, and meetings are organized for the interviews.
A common denominator for the companies in the research interview scope is that all hold a strong global presence, by operating in various countries and having distributed prod- uct development operations when considering all aspects, from research to product de- sign verification. Also, all the companies have thousands of employees and generate a yearly revenue of more than one billion euros. They all manufacture physical, industrial products. Inherent to product development, all these aspects make these companies equivalent to comparison as they all require certain necessities to have a frame of a product ready for manufacturing. Companies differ by the nature and the level of smart- ness in their product, which makes the findings of the interviews insightful. To summa- rize, the companies interviewed all have:
• Physical products to design and manufacture
• Need for concurrent engineering by global product development and engineering operations
• Thousands of employees and yearly revenue exceeding 1 BN EUR
The interviews were conducted with respondents from differing functions, to have insight on the varying perspectives when it comes to product development and engineering IT systems. The respondents are from IT, R&D, and business functions. Table 3 presents the interview scope by company characteristics.
Table 3. Research interview scope
Company Respondent Company info
IT R&D Busi ness
Products Employees Revenue
BN EUR
Operating countries
A X Sustainable fiber products for
various industries
8 000 2,9 14
B X Base stations & software 100 000 23,3 120
C X Smart technologies and lifecycle
solutions for the marine and en- ergy markets
19 000 5,2 80+
D X Technologies, automation and
services for the pulp, paper, and energy industries
14 000 3,7 30+
E X Various commercial products un-
der different brands. Home appliences, gardening, etc.
7 000 1,1 30
F X Healthcare solutions, devices,
and services
50 000 17,0 160+
G X Plants, systems, equipment, and
services, mainly for hydropower, pulp and paper industries
27 800 6,7 40+
H X Industrial cranes and hoists for
manufacturing and process indus- tries, shipyards, ports, and termi-
nals
16 900 3,2 50
I X Elevators, escalators, and auto-
matic building doors, as well as solutions for maintenance and
modernization
60 000 9,9 60+
The interviews were held by using an established frame of questions, but also inspiring open conversation, to have depth on the answers for gaining a somewhat personal view on the opinions of the respondent. The key focus areas were to identify the level of smartness on the products, how distributed are the product development and engineer- ing operations, how are the product development and engineering IT systems managed, does the current system scope support production prospects, and how organizational factors, such as competency outsourcing and external factors such as industry regula- tions are affecting the current operations.
3.2 Findings from the Manufacturing Industry
A common finding in the interviews is that most of the companies aim to have a more unified system scope, by fewer IT systems providers with more strong, strategic partner- ships. In practice this means that regardless of product group, geographical aspects, or volume, used product engineering systems in core product development processes are the same. Many of the companies in the research interview scope have a very long his- tory, and today’s business is a result of mergers and acquisitions, and this has a signifi- cant impact on diversity in the system scope. Commonly inorganic growth results in var- ious differing systems and databases are used. Differing systems and ways of working often presents a challenge when organizational culture faces continuous development, by widely adopting lean for example, which inherently promotes standardized working procedures.
All the respondents, except for one say that the management of IT systems is centralized for group IT organization. Although the distributed system management is said to be working for the company’s current business, there are weaknesses identified in this ap- proach. Information exchange is not effective enough, as the interoperability of the sys- tems is weak. This causes waste for some processes, and lean is adopted to mitigate the impact on product development and contributes more for transparency and efficiency than the current system scope. This company has no product service business, and product engineering systems are said to be highly customized. The statement that the distributed management still works for the current business underlines the connection of product development and holistic product lifecycle management. In this case the needs
derived from product lifecycle, especially from middle-of-life (MOL) to product engineer- ing is minor compared to companies where much of revenue stream is generated by product service, and very seamless data flow is a necessity. Many of the respondents saying that the IT system management is centralized highlight that smart architecture and interoperability of the systems is a pro for their product development.
70% of respondents says that their current product engineering systems supports their future production prospects, and the remaining 30% considered that the current scope does not support. The question was presented considering mid-term timeline of 3-5 years. One company presenting the minority group of 30% has mostly on-premise engi- neering systems from multiple vendors, and states that the interoperability and resilience in terms of how systems respond to change in volume are a con for product development.
For this company, a larger-scale IT transformation is ongoing, and systems hosted in private cloud are taking more foot place. Two companies out of the 70% highlight that the adoption of PLM system contributes the most on supporting future production pro- spects.
3.3 Summary of the Key Findings
For further development work, the key findings from the current state analysis are formed based on the objective to understand transformation potential and create a model to assess readiness for transition platform-based systems. Figure 3 consolidates the five key findings from the current state analysis. In addition to manufacturing companies, the key findings are supported by industry expert interviews.
Figure 3. The key findings from current state analysis
The key findings include internal and external elements impacting the decision making in an organization. Strategic partnerships, centralized IT organization, and PLM system adoption are factors arising from internal concerns regarding the overall business per- formance. Customer centricity and globality factors arise from external powers and leads to re-assessment of the current state of operations. The key findings are furthermore discussed and associated with the literature findings to comprise the overall transition model.
•”Our goal is to have more unified systems and less system providers, to go for strategic partners”
Strategic partnerships
•”Information exchange is not effective as it is, and interoperability of systems is weak, lean is adopted to mitigate”
Centralized IT organization
•“Customer expectations have changed, very specific design data is wanted, not just design drawings but source system data, system replications are important for customers”
Customer centricity
•“Digital transformation is enabling new business models, these are constantly under considerations, the goal is to have a seamless digital continuity and PLM plays a major role in this”
PLM system adoption
•“Still quite a challenge with many applications and tools. Global, concurrent design means that parallel up-to-date version of a design is always available”
Globality
4 Best Practice of Platform-based Product Engineering Solutions
This chapter provides a theoretical approach and literature’s view on product develop- ment and product engineering, particularly exploring the IT systems and tools. At first, smart connected products and changes in the industries are introduced. Common solu- tions and methods for product development and engineering are reviewed, to gain an understanding on favorable modern approaches based on literature findings. This is fol- lowed by a review on product information and product lifecycle management. Lastly, en- terprise maturity model and transformation potential according to existing models are covered for further association with the development work.
According to Porter and Heppelmann (2014: 1) IT is revolutionizing products and smart- connected products have unleashed a new era of competition. Prior to these smart-con- nected products, industrial products used to be a composition of mechanical and electri- cal parts. Due to IT as well as Operational Technology (OT) developments, these once conventional products have become more of a complex system, a combination of three core elements, physical components, smart components, and connectivity components.
Smart connected products offer exponentially expanding opportunities for companies that transcends the traditional boundaries of product functionalities and product service.
This very elementary level shift on a product is also disrupting value chains and forcing the companies to reassess internal processes and ways of working (Porter and Hep- pelmann 2014: 1-4).
Characteristics of the product impacts the product development and engineering by set- ting assumptions and needs for processes and technologies. Systems and tools used for developing the conventional product may become totally useless when the strategic decision is made to implement levels of smartness in the product. Porter and Hep- pelmann (2014: 2) argues that the smart, connected products raise a new set of strategic choices related to how value is created and captured and how all of the new generated data is utilized and managed during the lifecycle phases to achieve business benefits, through smart services as an example. Three core elements of smart-connected prod- ucts play a major role in this and are connected to enable some of the smart functional- ities to exist outside the physical product itself. Smart components amplify the capabili-
ties and values of physical components, and connectivity components amplify the capa- bilities and values of smart components. Figure 4 presents the three core elements of smart-connected products (Porter and Heppelmann 2014: 4).
Figure 4. Core elements of a smart-connected product (Porter and Heppelmann 2014: 4).
Developing a smart-connected product is not solely enough to capture the potential un- derlying value. New competencies and technologies are required and decisions for these must support the organizations business strategy. A necessity is a technology stack en- abling the smart-product development and operation as well as the collection, analysis and sharing of data generated in- and outside of a product. Technology stack comprises of multiple layers, including product hardware, embedded software, connectivity, a prod- uct cloud with remote servers, security tools, a gateway for external information sources and integrations with organizations business systems. Figure 5 visualizes an example of the technology stack for smart-connected products (Porter and Heppelmann 2014: 4-8).
Physical components Products mechanical and electrical parts
Smart components Sensors,
microprocessors, operating system and software
Connectivity components
Ports, antennaes and wireless protocols
Figure 5. Technology stack for smart-connected products (Porter and Heppelmann 2014: 6-7).
The product layer including the hardware and software constitutes a smart-connected product, which can be connected to product cloud. Now in parallel product data and smart applications can be run and this is enabling the potential value of smart-connected products, creating a connected environment with the attention in product lifecycle man- agement.
Product Product software Embedded OS, software, UI
Product hardware
Sensors, processors, ports / antennaes Connectivity
Network communication
Protocols enabling communication between product and product cloud Product cloud
Smart product applications Rules / analytics engine
Application platform Product data database
Figure 6. Product lifecycle management in smart-connected environment (Zhang et al. 2019:
3).
According to Zhang et al. (2019: 3) in smart-connected environments, product lifecycle management for complex products focuses on the complete product lifecycle, empha- sizing tracking and managing lifecycle data across the whole lifespan, particularly the usage stage. Product characteristics impact on product development is clear in these smart-connected environments. Product lifecycle data together with smart-connected product configurations and capabilities is restructuring the functions of product develop- ment, product manufacturing as well as product service, and seamless data flow is a necessity, as Figure 6 visualizes (Zhang et al. 2019: 2-4).
4.1 Product Development and Engineering
The favorable approach to product development and engineering is by managing a par- ametric product model. A parametric product model is created, maintained, and modified by IT tools which are developed for virtual prototyping purposes. Virtual prototyping is a simulation-based method that aims to help understanding better product behavior under varying circumstances and enables making design decisions in a virtual environment.
According to Chang (2015: 7) the virtual environment is a computational framework, in
which the geometric and physical properties of products are accurately simulated and represented. Common activities of virtual prototyping are parametric product modeling and simulations for performance as well as manufacturing. The starting point is con- structing a parametric product model, followed by product performance simulations and reliability evaluations. Manufacturing simulations can be carried out concurrently, and quality with costs obtained from these multidisciplinary simulations can be consolidated for review (Chang 2015: 7-11).
Computer Aided Design (CAD) software is the most common tool for constructing the parametric product model. Chang (2015: 7-8) describes that CAD product model is pa- rameterized by defining the dimensions which are used then to govern the geometry of the parts, and by establishing relations between the parts dimensions. These features make it easy and efficient for design engineers to explore design alternatives as the changes are automatically propagated throughout the mechanical design of the product, following the previously established dimensions and relations of the parts. Commonly, commercial CAD software includes features for structural geometry, loads, boundary conditions and material properties. In product development and engineering, a paramet- ric product model then evolves to a higher-fidelity level, and the legacy data from earlier product designs can be utilized in those operations. Product Data Management (PDM) features are established within commercial CAD software and can act as a basis for tool integration (Chang 2015: 7-10).
Simulations for product performance, reliability and manufacturing can be conducted concurrently after the product model is represented in CAD. Mappings governing changes from CAD models to simulations are needed for simulation model updates and for maintaining consistency between models during the design cycle. Tools performing the simulations for different purposes are Computer Aided Engineering (CAE) software, often dedicated to one or more aspects of engineering analysis, helping to solve for ex- ample structural and thermal problems. Chang (2015: 10-12) points out that the physics- based simulation technology has the potential to minimize the need for product hardware tests. Due to extensive product modeling and performed simulations with CAE software, unexpected defects are minimized during the actual hardware testing, thus mitigating the costs elevation (Chang 2015: 9-12).
The e-design paradigm
As Chang (2015: 5-7) describes, the e-design paradigm is a realization of concurrent engineering through virtual and physical prototyping with a systematic and quantitative method for design decision making. It specializes in performance and reliability assess- ment, and improvement of complex, large-scale, compute-intensive mechanical sys- tems. In practice, the paradigm is set out for shortening the overall product development cycle, improving product quality, and reducing related costs. It offers three value-adding concepts for product development and engineering (Chang 2015: 4).
• Bringing product performance, quality, and manufacturing cost for design consid- erations in the early design stage through virtual prototyping.
• Supporting design decision making based on quantitative product performance data.
• Incorporating physical prototyping techniques to support design verification and functional prototyping.
Product designed in the virtual environment can then be constructed to a physical proto- type directly from the CAD model, using rapid prototyping techniques such as 3D print- ing, and Computer Numerical Control (CNC) machining. A parametric product model de- signed in the virtual environment is essential and the backbone for the e-design, which is the favorable modern approach on new product development as well as product engi- neering. Some of the engineering analysis operations may need some specific simula- tion software to meet the needs of a certain ETO product, but mainly the used core de- sign tools for new product development and product engineering are the same, and based on a parametric product model, which allows concurrent changes across differing geographies.
Product Data and Information Management
Concurrent engineering made possible by tools such as CAD and CAE, and with design paradigms such as the e-design paradigm arises challenge for the generated data. Prod- uct data appears in very diverse forms, including text, numerical, graphics, CAD models, and in some cases even audio or video. Data needs to be available concurrently within and outside development and engineering functions, which needs effective manage- ment. Ong et al. (2008: 65) describes that Product Database Management is a process- oriented technology with a focus on the downstream information communication among and across product design departments. Information being stored and managed include engineering data such as CAD models, dimension drawings and associated documents, as well as various metadata, including owner of a file and status of information compo- nents. Furthermore, the major functionalities of a PDM system is described as follows (Ong et al. 2008: 65-66).
• Control of check-in and check-out of the product data to multiple users.
• Management of engineering change and release control on all versions/issues of components in a product.
• Building and manipulation of the product structure bill-of-material (BOM) for as- semblies.
• Assistance in configurations management of product variants.
• Corporation-wise management of complex products to spread product data over the entire PLM process.
In addition to various forms of product data, also data sources and responsibilities are commonly distributed within the organization. In his book Watts (2012: 94) identifies five common functions inside manufacturing company, with organizational responsibilities for product data. Yang (2007: 2) adds that product data arise at each stage in the product lifecycle and needs to be acquired and managed in an integrated and systematic manner to provide timely and accurate information to various stakeholders. Table 4 presents ex- amples of organizational responsibilities of product data.
Table 4. Organizational responsibilities of product data within manufacturing company (Watts 2012: 94).
Data Responsibility
Design documentation Design Engineering Support documentation Field Service Manufacturing documentation
(e.g. assembly instructions) Manufacturing, Product Management Quality documentation Quality Assurance
Packaging and catalog data Sales/Marketing
Watts (2012: 94-95) highlights the importance of BOM database in manufacturing com- panies. He even argues BOM being the most important piece of information for a manu- facturing company after the product specification. As mentioned in previous list of major PDM system functionalities by Ong et al. (2008: 65-66), BOM in its simplest definition, is a product structure. Watts (2012: 94-95) agrees by defining BOM as a compilation of parts lists. The product design is embodied in parts. Therefore, BOM can be viewed as recipe for a product. Whenever recipe changes or alternates, it needs to be maintained.
Watts (2012: 94) says that BOM is the heart of most manufacturing operations, and with its modern applications even more. BOM management enables product Configuration Management (CM), which is essential for most of the ETO products (Watts 2012: 94-96).
4.2 Product Lifecycle Management
Hadaya and Marchildon (2012: 1-2) states that organizations have recognized the im- portance of integrating operational activities between all the product’s stakeholders. Ad- ditionally, the importance of more integrated and cost-effective new product develop- ment, which are not suffering from side-effects of conventional design has led organiza- tions to adopt product lifecycle management approach. Product lifecycle management is an integrated, information-driven approach and comprises of people, processes, prac- tices, and technology. It addresses all the lifecycle phases of a product, starting from the design, to usage and culminating into removal and final disposal. Thus, the PLM ap- proach aims for the integrated management of product related information through the entire lifecycle, comprising of three phases (Hadaya and Marchildon 2012: 1-4).
• Beginning of life (BOL) including product concept, definition, design, manufactur- ing and selling.
• Middle of life (MOL) when the product is used, serviced, and maintained.
• End of life (EOL) during which the product can be refurbished, or its components and materials reassembled or reused.
Depiction by Radhakrishnan (2008: 36) that PLM software views the entire lifecycle of a product as a process, which can be managed, measured, monitored, and modified is indeed really accurate considering the holistic view on products life. PLM approach in- cludes a set of interrelated activities defined with certain types of inputs and outputs.
Additionally, there is a significant emphasis on partner involvement. PLM approach in- cludes involvement of many stakeholders, whether internal or external during products life. Externally these could mean contractors, suppliers, and customers. From processes point-of-view, external stakeholder involvement can have a role in for example require- ments management, change management and quality controlling. Figure 7 presents common PLM activities during the lifecycle phases (Hadaya and Marchildon 2012: 3-5).
Figure 7. Interrelated PLM activities (Hadaya and Marchildon 2012: 3-5).
PLM software system is a business system and exceeds the boundaries of systems ded- icated to engineering or information management. Still PLM system originated from two complementary applications, CAD and PDM, and developed beyond engineering and information related aspects. PLM system is a composition of functionalities to provide a
BOL
•Conceptual and detailed design
•Prototyping and design verification
•Process and production planning
MOL
•Managing delivery and assembly
•Maintenance and customer service
EOL
•Managing disassembly
•Disposal and recycling
shared platform for the creation, organization, and dissemination of product related knowledge across and outside the organization. Introduction of PLM is enabling organi- zations to shift from isolated applications to a set of systems, a platform for collaboration between product stakeholders. In other words, PLM is the backbone for transformation from application to platform-based approach. With its modern applications, PLM is a core business system of an organization (Hadaya and Marchildon 2012: 4-5).
4.3 Enterprise Maturity Model
In manufacturing companies PLM adoption is the step to achieve platform-based ap- proach, and when starting initiatives, it is important to understand the maturity level of an organization. There are vast amounts of existing models to assess maturity in a variety of contexts, with differing focus areas. The case company has developed an enterprise maturity model for assessing journey towards Model Based Enterprise (MBE). It is a four- step model, including seven identified levels of maturity. The enterprise maturity model shown in Table 5 focuses on identifying the current state and the key challenges faced by the organization in a certain level.
Table 5. Enterprise maturity model (Case company internal documentation).
Maturity definition
Maturity
level Current state Challenges
Model Based Enterprise
6 Externally connected, extended PLM, integrated manufacturing
Benefits leverage and transform- ing market leader in products and offerings
5 Internally connected PLM Return on Investment on the enter- prise-wide system/adoption
Model Based Definition
4
3D parametric fully annotated product models, digital manufac- turing
Customized process in PLM sys- tem for key departments
3
3D technical data packages and in- teractive viewable, CAx managed part-centric PLM
Customized process in PLM sys- tem for key departments
Model Centric
2 3D models create drawings and derivatives, document centric PDM
Less adoption of 3D in the enter- prise wide organization
No standard PLM systems
1 3D models create 2D drawings, document centric PDM
Product information in silos, risk of errors due to no concurrent prod- uct information available for suppli- ers
Drawing
centric 0 2D static drawings, ad-hoc models, file-sharing among functions
Standalone systems not communi- cating with each other, concurrent engineering not possible, risk of design and manufacturing mis- match
The enterprise maturity model does not assess the overall digital maturity of an organi- zation but focuses on the product development and engineering aspects. It is based on an idea of a model-based 3D enabled enterprise, where product development and engi- neering does not suffer from the product information silos and mismatches between dif- ferent BOM structures. The challenges faced by the organization in a certain level are presented in a common level and may vary depending on the company characteristics and industry. The highest maturity level definition, model-based enterprise includes four key objectives:
• Organized and available single source of product information through integrated IT systems environment
• Increased productivity and reduced human errors through 3D & automation in information transactions
• Access anytime and anywhere through complete digital user experience across personal devices
• Full spectrum supply chain integration through secure, consistent, and accessible product information & change communication
The enterprise maturity model is further on used as a tool on the development work phase and integrated to the proposed transition model, to achieve deeper level of under- standing on the current state of the potential customer companies. The maturity assess- ments are a co-created effort with the case company’s expert and part of the overall transformation potential assessment.
4.4 Transformation Potential
Digital transformation within the industries has been a hype topic for some time, and according to Stoianova (2020: 1) the focus of discussion is no more the necessity, but rather the assessment of readiness for digital transformation. This complex phenomenon is at present incorporating high expectations regarding quality of services and increased competitiveness, as well as high concerns regarding new professions, job loses, and threats of information security. Success with transformation is about making the right strategic bets, and only 33% of organizations successfully meet the challenge of digital disruption (BCG 2021).
Companies are widely using different ways to determine their digital maturity and readi- ness for transformation, and lots of different models are introduced. The four dimensions from the model by Forrester (2016: 3) shown in Figure 8 evaluates organizations digital sophistication and aims at helping with assessing overall digital readiness. Each dimen- sion focuses on evaluating the core capabilities, attitudes, and competencies that define a mature digital operation (Forrester 2016: 2-3).
Figure 8. Four dimensions determine digital maturity (Forrester 2016: 3).
Culture Approach to digitally driven
innovation
Technology Adoption of emerging technology
Organization Support for digital strategy,
governance, and execution
Insights Customer and business data to
measure success and inform strategy
Boston Consulting Group identifies three key phases of digital transformation as blue- printing the high-level strategy, activating the initiatives, and scaling across the organi- zation. According to their experiences, much of the unsuccessful transformation cases can be traced back to the first key phase, insufficient definition of digital strategy. It is found that organizations often suffer the lack of insight on the key opportunities and threats, and thus the high-level strategy ends up inadequate. The importance of holistic view of what digital means for company’s business at both strategic and technical levels is underlined. To tackle these problems in the blueprinting phase, Boston Consulting Group has designed their digital strategy model incorporating four core enablers shown in Figure 9 (BCG 2021).
Figure 9. Core enablers for a digital strategy (BCG 2021).
Transition to platform-based solutions with product development and engineering sys- tems in an organization wide-scale means IT and digital transformation, as the core busi- ness systems are affected. The starting point should be considering the business needs and rethinking of processes and ways of working is essential. The four dimensions on
Organization Talent, structure
& ways of working
Assets Technology,
data, capabilities
Ecosystem Partnerships,
M&A
Portfolio Businesses,
parenting
the Forrester model and four core enablers on the BCG model are essential for the tran- sition model development work, for identifying the characteristics impacting the transfor- mation readiness.
The current state analysis findings together with the available knowledge and best prac- tice discovered from the literature compose the conceptual framework of the thesis, shown in Figure 10. It is furthermore used as a tool in the development work and as a bases for the transition model attributes.
Figure 10. The conceptual framework
The transition factors of the conceptual framework include internal and external powers affecting the transformation potential. The conceptual framework aims to integrate all the key findings to prevent biased view. This is further on demonstrated on the next chapter, describing the transition model attributes.
Industry Product System scope and
infra Business and
organization Transition factor
External forces such as power of customers and industry regulations are at the core of
digital transformation Product characteristics such as complexity and smartness have significant impact on the overall IT
system requirements Challenges of concurrent engineering and globality forces
companies to re-assess the applicability of current systems
Business models and organizational factors have
significant impact on the transformation readiness
Findings
CSA Porter and Heppelmann 2014.
Porter and Heppelmann 2015.
Shou et al. 2019
Porter and Heppelmann 2015.
Case company internal documentation
Porter and Heppelmann 2014.
Pessot et al. 2020.
Hadaya and Marchildon 2012.
Related theory
5 Transition to Platform-based Solutions
This chapter covers transition model development and results. The chapter presents how the development work was conducted and how it integrates the current state analysis findings with the literature review. Lastly, the chapter presents the transition model pro- posal with maturity assessments using the case company’s enterprise maturity model and the data derived from the interviews. The chapter also explains how the model was simulated with the group of companies.
5.1 Development Work
The proposed transition model aims to meet the thesis objective by assessing the trans- formation readiness through characteristics. The following sub-chapters consolidate the key findings from CSA as well as literature and lastly integrate the above-mentioned maturity assessments to provide more depth for the model.
Figure 11. Building blocks for transition model development
Conceptual framework
- Business & organization - System scope & infra - Product
- Industry
Transition model Stakeholder input (Data 2)
- Interview with Program Manager, Mechanical Design & Simulation
- Enterprise maturity assessments - Identification of challenges - Primary deliverables
Experiences from industries
(Data 1)
- Strategic partnerships - PLM system adoption - Centralized IT
organization - Globality
- Customer centricity
As seen in Figure 11, the development work for the transition model consists of three key building blocks. Transition model includes 11 attributes which are derived from the current state analysis and literature review, and furthermore validated with the case com- pany expert interviews. The attributes are structured under four attribute groups repre- senting the conceptual framework:
• Business and organization
• System scope and infra
• Product
• Industry
The current state analysis findings were discussed, and the enterprise maturity assess- ments co-created in the interview with the case company’s expert, Program Manager from Mechanical Design & Simulation. This phase refers to the Data 2 collection, and the objective was to identify the primary deliverables to create a portfolio-focus view for the transition model. Additionally, the conceptual framework that forms the transition model attribute groups and attributes were discussed. The key take-aways of this inter- view are consolidated in the next sub-chapters and within the transition model proposal, visualized in Figure 12.
5.1.1 Business and Organization
Findings from the current state analysis indicate that companies which have adopted the PLM system as a backbone for their product management leverage from transparency and harmonized ways of working, system usage complements organizations business strategy. Hadaya and Marchildon (2012: 4) stated that introduction of PLM enabled or- ganizations to shift from isolated applications to a set of systems. With dedicated PLM teams, organizations can widen PLM adoption, deploy custom solutions and scale fast.
New technology requires talent management, and according to Pessot et al. (2020: 9) it must be priority goal to increase knowledge base with skills aimed at proper use of tech- nology and overcome resistance to change by eliminating lack of expertise among em- ployees. The implementation of PLM requires strategy and competences, and organiza- tions with PLM system in use are more ready for transformation and realized business benefits. The following quotes are from the current state analysis interviews and highlight the benefits of PLM adoption for the organization.
PLM initiative has been driving the harmonization of tools and ways of working (CSA).
Digital transformation is enabling new business models, these are constantly un- der considerations, the goal is to have a seamless digital continuity, PLM plays a major role in this (CSA).
After-sales services generates major revenues and smart service creation is one modern business need driving organizations to transform managerial and operational activities.
Porter and Heppelmann (2014: 3) describes the third wave of IT-driven competition in- cluding IT becoming an integral part of the product itself through connectivity and smart elements, coupled with product cloud where applications can be run. This is driving dra- matic improvements, enabled by increased amounts of product usage data. As an ex- ample, through these smart applications, first-time-fix rate can be increased when field engineer is dispatched with correct parts and tools for maintenance. To succeed with service-oriented product, competences and smart architecture needs to be aligned. Op- timization of customer interaction and integrated services through enabling technologies allows companies to deepen the relationship and induce more empowered end-custom- ers (Pessot et al. 2020: 9-11).
5.1.2 System Scope and Infra
The current state analysis interviews showed that most of the companies aim to harmo- nize system scope by fewer system providers with more strong strategic partnerships. In few cases, current state of disjointed systems and databases is a result from mergers and acquisitions. Although this was not a consensus finding, it shows that in most cases the transformation is driven by restraining the system providers to strategic partners ra- ther than fostering multiple supplier relations. The MIT Sloan Management Review’s re- search with Deloitte underlines that strategy, not technology drives digital transformation (Kane et al. 2015: 6).
Expected key benefits of cloud computing includes greater flexibility, better mobility &
information access, and cost reductions through optimized utilization & ICT employee reduction (Shou et al. 2019: 12). The current state analysis findings indicate that some of the organizations may encounter some restrictions on cloud-based systems and data storing. Industry regulations and contracts between stakeholders can dictate where data needs to be stored, and this could limit usage of public cloud systems. Regardless it is
evident that adoption of cloud-based systems contributes to transformation readiness when the information access is mobilized rather than restrained by stand-alone systems.
5.1.3 Product
Porter and Heppelmann (2015: 9) says that the smart connected products require re- thinking of design. Core functions like product development, IT, and manufacturing are being redefined by the changes in the work procedures and new functions are emerging to answer the needs of, for example increasing quantities of product data available. In- terviews showed that companies are aware of the impact of product characteristics to their business, and in many cases identified that increased complexity in products has resulted in increased complexity in system requirements. Complexity of a configurable product can stratify over time so that the maintenance costs of product configurator ele- vates in an uncontrollable way. Complexity needs to be managed top-down, considering the business needs, rather than just expanding complexity in accordance with techno- logical possibilities.
Deployment of digital twin technology is an excellent utilization of new rich data gener- ated by smart connected products. It provides inputs into how products can be better designed, manufactured, and serviced (Porter and Heppelmann 2015: 9). High level of complexity and smartness in the product drives transformation rather than very simple product composed of physical parts alone.
5.1.4 Industry
From the current state analysis interviews it was found that there are significant differ- ences on regulations between industries, and this affects how companies must produce, maintain, and distribute product information and data, especially during the beginning- and middle-of-life. These requirements vary a lot depending on the industry, healthcare and construction represents one of the most regulated. Power of customers is a similar external force affecting the product development and engineering systems. Customer centricity is one of the key findings from the industries. Requirements and expectations have changed and to foster the relations, organizations must re-assess the applicability of current systems and processes against customer needs.
5.2 Transition Model Proposal
Based on the findings from the literature as well as the current state analysis, the follow- ing attributes compose the transition model, assessing readiness for transformation to- wards platform-based approach. Table 6 consolidates attribute groups, attributes, attrib- ute statements and research sources for the transition model.
